| 1. |
- Almeida, Diogo, 1991-, et al.
(författare)
-
Team KTH’s Picking Solution for the Amazon Picking Challenge 2016
- 2017
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Ingår i: Warehouse Picking Automation Workshop 2017.
-
Konferensbidrag (populärvet., debatt m.m.)abstract
- In this work we summarize the solution developed by Team KTH for the Amazon Picking Challenge 2016 in Leipzig, Germany. The competition simulated a warehouse automation scenario and it was divided in two tasks: a picking task where a robot picks items from a shelf and places them in a tote and a stowing task which is the inverse task where the robot picks items from a tote and places them in a shelf. We describe our approach to the problem starting from a high level overview of our system and later delving into details of our perception pipeline and our strategy for manipulation and grasping. The solution was implemented using a Baxter robot equipped with additional sensors.
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| 2. |
- Almeida, Diogo, 1991-, et al.
(författare)
-
Team KTH’s Picking Solution for the Amazon Picking Challenge 2016
- 2020
-
Ingår i: Advances on Robotic Item Picking: Applications in Warehousing and E-Commerce Fulfillment. - Cham : Springer Nature. ; , s. 53-62
-
Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- In this chapter we summarize the solution developed by team KTH for the Amazon Picking Challenge 2016 in Leipzig, Germany. The competition, which simulated a warehouse automation scenario, was divided into two parts: a picking task, where the robot picks items from a shelf and places them into a tote, and a stowing task, where the robot picks items from a tote and places them in a shelf. We describe our approach to the problem starting with a high-level overview of the system, delving later into the details of our perception pipeline and strategy for manipulation and grasping. The hardware platform used in our solution consists of a Baxter robot equipped with multiple vision sensors.
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| 3. |
- Andersson, Klas, 1968-
(författare)
-
Improving Fixed Wing UAV Endurance, by Cooperative Autonomous Soaring
- 2021
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The ever-expanding use and development of smaller UAVs (Unmanned Aerial Vehicles) has highlighted an increasing demand for extended range and endurance for this type of vehicles. In this thesis, the development of a concept and system for autonomous soaring of cooperating unmanned aerial vehicles is presented. The purpose of the developed system is to extend endurance by harvesting energy available in the atmosphere in the form of thermal updrafts, in a similar way that some birds and manned gliders do. By using this “free” energy, considerable improvements in maximum achievable endurance can be realized under a wide variety of atmospherical and weather conditions. The work included theoretical analysis, simulations, and finally flight test- ing of the soaring controller and the system. The system was initially devel- oped as a single-vehicle concept and thereafter extended into a system consist- ing of two cooperating gliders. The purpose of the extension to cooperation, was to further improve the performance of the system by increasing the ability to locate the rising air of thermal updrafts. The theoretical analysis proved the soaring algorithm’s thermal centering controller to be stable. The trials showed the concept of autonomous soaring to function as expected from the simulations. Further it revealed that, by applying the idea, extensive performance gains can be achieved under a fairly wide variety of conditions. The cooperative soaring, likewise, functioned as anticipated and the glid- ers found, cooperated, and climbed together in updrafts. This represents the first and presumably only time cooperative autonomous soaring in this way, has been successfully demonstrated in flight. To draw further conclusions on the advantages of cooperative soaring additional flight trials would, however, be beneficial. Possible issues and limitations were highlighted during the trials and a number of potential improvements were identified. As a part of the work, trials were conducted to verify the viability to implement the system into “real world” operational scenarios. As a proof of concept this was done by tasking the autonomous gliders to perform data/communications relay missions for other UAV systems sending imagery to the ground-station from beyond line of sight (BLOS). The outcome of the trials was positive and the concept appeared to be well suited for these types of missions. The comms relay system was further developed into a hybrid system where the optimal location concerning relay performance was autonomously sought out, after-which the attentiveness then switched to autonomous thermal soaring in the vicinity of this ideal relay position. The hybrid system was tested in simulation and partially flight tested.
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| 4. |
- Anisi, David A., 1977-, et al.
(författare)
-
Communication constrained multi-UGV surveillance
- 2008
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Ingår i: IFAC World Congress. - Seoul, Korea.
-
Konferensbidrag (refereegranskat)abstract
- This paper addresses the problem of connectivity constrained surveillance of a given polyhedral area with obstacles using a group of Unmanned Ground Vehicles (UGVs). The considered communication restrictions may involve both line-of-sight constraints and limited sensor range constraints. In this paper, the focus is on dynamic information graphs, G, which are required to be kept recurrently connected. The main motivation for introducing this weaker notion of connectivity is security and surveillance applications where the sentry vehicles may have to split temporary in order to complete the given mission efficiently but are required to establish contact recurrently in order to exchange information or to make sure that all units are intact and well-functioning. From a theoretical standpoint, recurrent connectivity is shown to be sufficient for exponential convergence of consensus filters for the collected sensor data.
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| 5. |
- Anisi, David A., et al.
(författare)
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Cooperative Minimum Time Surveillance With Multiple Ground Vehicles
- 2010
-
Ingår i: IEEE Transactions on Automatic Control. - 0018-9286 .- 1558-2523. ; 55:12, s. 2679-2691
-
Tidskriftsartikel (refereegranskat)abstract
- In this paper, we formulate and solve two different minimum time problems related to unmanned ground vehicle (UGV) surveillance. The first problem is the following. Given a set of surveillance UGVs and a polyhedral area, find waypoint-paths for all UGVs such that every point of the area is visible from a point on a path and such that the time for executing the search in parallel is minimized. Here, the sensors' field of view are assumed to have a limited coverage range and be occluded by the obstacles. The second problem extends the first by additionally requiring the induced information graph to be connected at the time instants when the UGVs perform the surveillance mission, i.e., when they gather and transmit sensor data. In the context of the second problem, we also introduce and utilize the notion of recurrent connectivity, which is a significantly more flexible connectivity constraint than, e.g., the 1-hop connectivity constraints and use it to discuss consensus filter convergence for the group of UGVs.
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| 6. |
- Anisi, David A., 1977-, et al.
(författare)
-
Minimum time multi-UGV surveillance
- 2008
-
Ingår i: OPTIMIZATION AND COOPERATIVE CONTROL STRATEGIES. - Berlin : Springer Verlag. - 9783540880622 ; , s. 31-45
-
Konferensbidrag (refereegranskat)abstract
- This paper addresses the problem of concurrent task- and path planning for a number of surveillance Unmanned Ground Vehicles (UGVs) such that a user defined area of interest is covered by the UGVs' sensors in minimum time. We first formulate the problem, and show that it is in fact a generalization of the Multiple Traveling Salesmen Problem (MTSP), which is known to be NP-hard. We then propose a solution that decomposes the problem into three subproblems. The first is to find a maximal convex covering of the search area. Most results on static coverage use disjoint partitions of the search area, e.g. triangulation, to convert the continuous sensor positioning problem into a discrete one. However, by a simple example, we show that a highly overlapping set of maximal convex sets is better suited for minimum time coverage. The second subproblem is a combinatorial assignment and ordering of the sets in the cover. Since Tabu search algorithms are known to perform well on various routing problems, we use it as a part of our proposed solution. Finally, the third subproblem utilizes a particular shortest path sub-routine in order to find the vehicle paths, and calculate the overall objective function used in the Tabu search. The proposed algorithm is illustrated by a number of simulation examples.
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| 7. |
- Anisi, David, et al.
(författare)
-
Online Trajectory Planning for Aerial Vehicle : A Safe Approach with Guaranteed Task Completion
-
Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- On-line trajectory optimization in three dimensional space is the main topic of the paper at hand. The high-level framework augments on-line receding horizon control with an off-line computed terminal cost that captures the global characteristics of the environment, as well as any possible mission objectives. The first part of the paper is devoted to the single vehicle case while the second part considers the problem of simultaneous arrival of multiple aerial vehicles. The main contribution of the first part is two-fold. Firstly, by augmenting a so called safety maneuver at the end of the planned trajectory, this paper extends previous results by addressing provable safety properties in a 3D setting. Secondly, assuming initial feasibility, the planning method presented is shown to have finite time task completion. Moreover, a quantitative comparison between the two competing objectives of optimality and computational tractability is made. Finally, some other key characteristics of the trajectory planner, such as ability to minimize threat exposure and robustness, are highlighted through simulations. As for the simultaneous arrival problem considered in the second part, by using a time-scale separation principle, we are able to adopt standard Laplacian control to a consensus problem which is neither unconstrained, nor first order.
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| 8. |
- Bhat, Sriharsha, 1991-, et al.
(författare)
-
A Cyber-Physical System for Hydrobatic AUVs : System Integration and Field Demonstration
- 2020
-
Ingår i: 2020 IEEE/OES Autonomous Underwater Vehicles Symposium, AUV 2020. - : Institute of Electrical and Electronics Engineers (IEEE).
-
Konferensbidrag (refereegranskat)abstract
- Cyber-physical systems (CPSs) comprise a network of sensors and actuators that are integrated with a computing and communication core. Hydrobatic Autonomous Underwater Vehicles (AUVs) can be efficient and agile, offering new use cases in ocean production, environmental sensing and security. In this paper, a CPS concept for hydrobatic AUVs is validated in real-world field trials with the hydrobatic AUV SAM developed at the Swedish Maritime Robotics Center (SMaRC). We present system integration of hardware systems, software subsystems for mission planning using Neptus, mission execution using behavior trees, flight and trim control, navigation and dead reckoning. Together with the software systems, we show simulation environments in Simulink and Stonefish for virtual validation of the entire CPS. Extensive field validation of the different components of the CPS has been performed. Results of a field demonstration scenario involving the search and inspection of a submerged Mini Cooper using payload cameras on SAM in the Baltic Sea are presented. The full system including the mission planning interface, behavior tree, controllers, dead-reckoning and object detection algorithm is validated. The submerged target is successfully detected both in simulation and reality, and simulation tools show tight integration with target hardware.
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| 9. |
- Bhat, Sriharsha, et al.
(författare)
-
A Cyber-Physical System for Hydrobatic AUVs: System Integration and Field Demonstration
- 2020
-
Konferensbidrag (refereegranskat)abstract
- Cyber-physical systems (CPSs) comprise a network of sensors and actuators that are integrated with a computing and communication core. Hydrobatic Autonomous Underwater Vehicles (AUVs) can be efficient and agile, offering new use cases in ocean production, environmental sensing and security. In this paper, a CPS concept for hydrobatic AUVs is validated in real-world field trials with the hydrobatic AUV SAM developed at the Swedish Maritime Robotics Center (SMaRC). We present system integration of hardware systems, software subsystems for mission planning using Neptus, mission execution using behavior trees, flight and trim control, navigation and dead reckoning. Together with the software systems, we show simulation environments in Simulink and Stonefish for virtual validation of the entire CPS. Extensive field validation of the different components of the CPS has been performed. Results of a field demonstration scenario involving the search and inspection of a submerged Mini Cooper using payload cameras on SAM in the Baltic Sea are presented. The full system including the mission planning interface, behavior tree, controllers, dead-reckoning and object detection algorithm is validated. The submerged target is successfully detected both in simulation and reality, and simulation tools show tight integration with target hardware.
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| 10. |
- Båberg, Fredrik, et al.
(författare)
-
Extended version of Adaptive Object Centered Teleoperation Control of a Mobile Manipulator
-
Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Teleoperation of a mobile robot manipulating and exploring an object shares many similarities with the manipulation of virtual objects in a 3D design software such as AutoCAD. The user interfaces are however quite different, mainly for historical reasons. In this paper we aim to change that, and draw inspiration from the 3D design community to propose a teleoperation interface control mode that is identical to the ones being used to locally navigate the virtual viewpoint of most Computer Aided Design (CAD)softwares.The proposed mobile manipulator control framework thus allows the user to focus on the 3D objects being manipulated, using control modes such as orbit object and pan object. The gripper of the robot performs the desired motions relative to the object, while the manipulator arm and base moves in a way that realizes the desired gripper motions. The system redundancies are exploited in order to take additional constraints, such as obstacle avoidance, into account, using a constraint based programming framework.
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| 11. |
- Båberg, Fredrik
(författare)
-
Improving Manipulation and Control of Search and Rescue UGVs Operating Across Autonomy Levels
- 2022
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Robots are often used for “dirty, dull and dangerous” jobs, where time, money or lives can be saved. A field with dangerous situations is search and rescue, with structural collapses and toxic environment. In those situations, robots have the potential to save lives.In this thesis we discuss improvements to unmanned ground vehicles (UGVs) for search and rescue in terms of manipulation and control. From the use of developments in video games for teleoperation, presentation of signal strength prediction, to ideas from 3D CAD for inspection tasks, and finally formation keeping for mobile manipulators. The problems will be addressed at different autonomy levels, regarding the robot operator interaction.We first consider teleoperation of an unmanned ground vehicle. Through a user study we compare two control modes, the traditional Tank Control and the video game inspired Free Look Control. Then, knowing how important connectivity is for teleoperation, where low connectivity can lead to the robot being abandoned, we propose a user interface which combines predicted radio signal strength with Free Look Control.Next we consider teleoperation of a mobile manipulator, which allows for inspection tasks. This adds complexity to the operator in terms of control, where not only the platform itself, but also the manipulator, has to be controlled. Inspired by 3D CAD software, where a core functionality is inspection of an object, we propose the control method Orbit Control. The system can assist with controlling some degrees of freedom of the robot, while the operator focuses on the final inspection and interaction.Finally, we consider a group of mobile manipulators transporting a larger object in a high obstacle density environment. A partially collapsed structure can contain areas which are not suitable to move in. To find a path for navigation, moving information while avoiding obstacles, can be challenging. We propose a combination of rapidly-exploring random tree (RRT) and constraint based programming, leading to a more efficient approach at high obstacle densities.
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| 12. |
- Caccamo, Sergio, 1987-
(författare)
-
Enhancing geometric maps through environmental interactions
- 2018
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The deployment of rescue robots in real operations is becoming increasingly commonthanks to recent advances in AI technologies and high performance hardware. Rescue robots can now operate for extended period of time, cover wider areas andprocess larger amounts of sensory information making them considerably more usefulduring real life threatening situations, including both natural or man-made disasters.In this thesis we present results of our research which focuses on investigating ways of enhancing visual perception for Unmanned Ground Vehicles (UGVs) through environmental interactions using different sensory systems, such as tactile sensors and wireless receivers.We argue that a geometric representation of the robot surroundings built upon vision data only, may not suffice in overcoming challenging scenarios, and show that robot interactions with the environment can provide a rich layer of new information that needs to be suitably represented and merged into the cognitive world model. Visual perception for mobile ground vehicles is one of the fundamental problems in rescue robotics. Phenomena such as rain, fog, darkness, dust, smoke and fire heavily influence the performance of visual sensors, and often result in highly noisy data, leading to unreliable or incomplete maps.We address this problem through a collection of studies and structure the thesis as follow:Firstly, we give an overview of the Search & Rescue (SAR) robotics field, and discuss scenarios, hardware and related scientific questions.Secondly, we focus on the problems of control and communication. Mobile robotsrequire stable communication with the base station to exchange valuable information. Communication loss often presents a significant mission risk and disconnected robotsare either abandoned, or autonomously try to back-trace their way to the base station. We show how non-visual environmental properties (e.g. the WiFi signal distribution) can be efficiently modeled using probabilistic active perception frameworks based on Gaussian Processes, and merged into geometric maps so to facilitate the SAR mission. We then show how to use tactile perception to enhance mapping. Implicit environmental properties such as the terrain deformability, are analyzed through strategic glancesand touches and then mapped into probabilistic models.Lastly, we address the problem of reconstructing objects in the environment. Wepresent a technique for simultaneous 3D reconstruction of static regions and rigidly moving objects in a scene that enables on-the-fly model generation. Although this thesis focuses mostly on rescue UGVs, the concepts presented canbe applied to other mobile platforms that operates under similar circumstances. To make sure that the suggested methods work, we have put efforts into design of user interfaces and the evaluation of those in user studies.
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| 13. |
- Caccamo, Sergio, et al.
(författare)
-
RCAMP : A Resilient Communication-Aware Motion Planner for Mobile Robots with Autonomous Repair of Wireless Connectivity
- 2017
-
Ingår i: 2017 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS). - : IEEE. - 9781538626825 ; , s. 2010-2017
-
Konferensbidrag (refereegranskat)abstract
- Mobile robots, be it autonomous or teleoperated, require stable communication with the base station to exchange valuable information. Given the stochastic elements in radio signal propagation, such as shadowing and fading, and the possibilities of unpredictable events or hardware failures, communication loss often presents a significant mission risk, both in terms of probability and impact, especially in Urban Search and Rescue (USAR) operations. Depending on the circumstances, disconnected robots are either abandoned, or attempt to autonomously back-trace their way to the base station. Although recent results in Communication-Aware Motion Planning can be used to effectively manage connectivity with robots, there are no results focusing on autonomously re-establishing the wireless connectivity of a mobile robot without back-tracing or using detailed a priori information of the network. In this paper, we present a robust and online radio signal mapping method using Gaussian Random Fields, and propose a Resilient Communication-Aware Motion Planner (RCAMP) that integrates the above signal mapping framework with a motion planner. RCAMP considers both the environment and the physical constraints of the robot, based on the available sensory information. We also propose a self-repair strategy using RCMAP, that takes both connectivity and the goal position into account when driving to a connection-safe position in the event of a communication loss. We demonstrate the proposed planner in a set of realistic simulations of an exploration task in single or multi-channel communication scenarios.
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| 14. |
- Colledanchise, Michele, et al.
(författare)
-
Obstacle avoidance in formation using navigation-like functions and constraint based programming
- 2013
-
Ingår i: Proceedings of the International Conference on Intelligent Robots and Systems (IROS), 2013 IEEE/RSJ. - : IEEE conference proceedings. - 9781467363587 ; , s. 5234-5239
-
Konferensbidrag (refereegranskat)abstract
- In this paper, we combine navigation functionlike potential fields and constraint based programming to achieve obstacle avoidance in formation. Constraint based programming was developed in robotic manipulation as a technique to take several constraints into account when controlling redundant manipulators. The approach has also been generalized, and applied to other control systems such as dual arm manipulators and unmanned aerial vehicles. Navigation functions are an elegant way to design controllers with provable properties for navigation problems. By combining these tools, we take advantage of the redundancy inherent in a multi-agent control problem and are able to concurrently address features such as formation maintenance and goal convergence, even in the presence of moving obstacles. We show how the user can decide a priority ordering of the objectives, as well as a clear way of seeing what objectives are currently addressed and what are postponed. We also analyze the theoretical properties of the proposed controller. Finally, we use a set of simulations to illustrate the approach.
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| 15. |
- Colledanchise, Michele, et al.
(författare)
-
Towards Blended Reactive Planning and Acting using Behavior Trees
- 2019
-
Ingår i: 2019 International Conference on Robotics And Automation (ICRA). - : IEEE Robotics and Automation Society. - 9781538660263 ; , s. 8839-8845
-
Konferensbidrag (refereegranskat)abstract
- In this paper, we show how a planning algorithm can be used to automatically create and update a Behavior Tree (BT), controlling a robot in a dynamic environment. The planning part of the algorithm is based on the idea of back chaining. Starting from a goal condition we iteratively select actions to achieve that goal, and if those actions have unmet preconditions, they are extended with actions to achieve them in the same way. The fact that BTs are inherently modular and reactive makes the proposed solution blend acting and planning in a way that enables the robot to effectively react to external disturbances. If an external agent undoes an action the robot re- executes it without re-planning, and if an external agent helps the robot, it skips the corresponding actions, again without re- planning. We illustrate our approach in two different robotics scenarios.
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| 16. |
- Colledancise, Michele, et al.
(författare)
-
Learning of Behavior Trees for Autonomous Agents
- 2018
-
Ingår i: IEEE Transactions on Games. - : IEEE Press. - 2475-1502.
-
Tidskriftsartikel (refereegranskat)abstract
- In this paper, we study the problem of automatically synthesizing a successful Behavior Tree (BT) in an a-priori unknown dynamic environment. Starting with a given set of behaviors, a reward function, and sensing in terms of a set of binary conditions, the proposed algorithm incrementally learns a switching structure in terms of a BT, that is able to handle the situations encountered. Exploiting the fact that BTs generalize And-Or-Trees and also provide very natural chromosome mappings for genetic pro- gramming, we combine the long term performance of Genetic Programming with a greedy element and use the And-Or analogy to limit the size of the resulting structure. Finally, earlier results on BTs enable us to provide certain safety guarantees for the resulting system. Using the testing environment Mario AI we compare our approach to alternative methods for learning BTs and Finite State Machines. The evaluation shows that the proposed approach generated solutions with better performance, and often fewer nodes than the other two methods.
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| 17. |
- Iovino, Matteo, et al.
(författare)
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A survey of Behavior Trees in robotics and AI
- 2022
-
Ingår i: Robotics and Autonomous Systems. - : Elsevier BV. - 0921-8890 .- 1872-793X. ; 154
-
Tidskriftsartikel (refereegranskat)abstract
- Behavior Trees (BTs) were invented as a tool to enable modular AI in computer games, but have received an increasing amount of attention in the robotics community in the last decade. With rising demands on agent AI complexity, game programmers found that the Finite State Machines (FSM) that they used scaled poorly and were difficult to extend, adapt and reuse. In BTs, the state transition logic is not dispersed across the individual states, but organized in a hierarchical tree structure, with the states as leaves. This has a significant effect on modularity, which in turn simplifies both synthesis and analysis by humans and algorithms alike. These advantages are needed not only in game AI design, but also in robotics, as is evident from the research being done. In this paper we present a comprehensive survey of the topic of BTs in Artificial Intelligence and Robotic applications. The existing literature is described and categorized based on methods, application areas and contributions, and the paper is concluded with a list of open research challenges.
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| 18. |
- Kartasev, Mart, et al.
(författare)
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Improving the Performance of Backward Chained Behavior Trees that use Reinforcement Learning
- 2023
-
Ingår i: 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2023. - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 1572-1579
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Konferensbidrag (refereegranskat)abstract
- In this paper we show how to improve the performance of backward chained behavior trees (BTs) that include policies trained with reinforcement learning (RL). BTs represent a hierarchical and modular way of combining control policies into higher level control policies. Backward chaining is a design principle for the construction of BTs that combines reactivity with goal directed actions in a structured way. The backward chained structure has also enabled convergence proofs for BTs, identifying a set of local conditions to be satisfied for the convergence of all trajectories to a set of desired goal states. The key idea of this paper is to improve performance of backward chained BTs by using the conditions identified in a theoretical convergence proof to configure the RL problems for individual controllers. Specifically, previous analysis identified so-called active constraint conditions (ACCs), that should not be violated in order to avoid having to return to work on previously achieved subgoals. We propose a way to set up the RL problems, such that they do not only achieve each immediate subgoal, but also avoid violating the identified ACCs. The resulting performance improvement depends on how often ACC violations occurred before the change, and how much effort, in terms of execution time, was needed to re-achieve them. The proposed approach is illustrated in a dynamic simulation environment.
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| 19. |
- Kartasev, Mart, et al.
(författare)
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Improving the Performance of Learned Controllers in Behavior Trees Using Value Function Estimates at Switching Boundaries
- 2024
-
Ingår i: IEEE Robotics and Automation Letters. - : Institute of Electrical and Electronics Engineers (IEEE). - 2377-3766. ; 9:5, s. 4647-4654
-
Tidskriftsartikel (refereegranskat)abstract
- Behavior trees offer a modular approach to developing an overall controller from a set of sub-controllers that solve different sub-problems. These sub-controllers can be created using various methods, such as classical model-based control or reinforcement learning (RL). To achieve the overall goal, each sub-controller must satisfy the preconditions of the next sub-controller. Although every sub-controller may be locally optimal in achieving the preconditions of the next one, given some performance metric like completion time, the overall controller may still not be optimal with respect to the same performance metric. In this paper, we demonstrate how the performance of the overall controller can be improved if we use approximations of value functions to inform the design of a sub-controller of the needs of the next controller. We also show how, under certain assumptions, this leads to a globally optimal controller when the process is executed on all sub-controllers. Finally, this result also holds when some of the sub-controllers are already given. This means that if we are constrained to use some existing sub-controllers, the overall controller will be globally optimal, given this constraint.
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| 20. |
- Kruijff-Korbayová, I, et al.
(författare)
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TRADR Project : Long-Term Human-Robot Teaming for Robot Assisted Disaster Response
- 2015
-
Ingår i: Künstliche Intelligenz. - : Springer. - 0933-1875 .- 1610-1987. ; 29:2, s. 193-201
-
Tidskriftsartikel (refereegranskat)abstract
- This paper describes the project TRADR: Long-Term Human-Robot Teaming for Robot Assisted Disaster Response. Experience shows that any incident serious enough to require robot involvement will most likely involve a sequence of sorties over several hours, days and even months. TRADR focuses on the challenges that thus arise for the persistence of environment models, multi-robot action models, and human-robot teaming, in order to allow incremental capability improvement over the duration of a mission. TRADR applies a user centric design approach to disaster response robotics, with use cases involving the response to a medium to large scale industrial accident by teams consisting of human rescuers and several robots (both ground and airborne). This paper describes the fundamentals of the project: the motivation, objectives and approach in contrast to related work.
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| 21. |
- Nimara, Doumitrou Daniil, et al.
(författare)
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Model-Based Reinforcement Learning for Cavity Filter Tuning
- 2023
-
Ingår i: Proceedings of the 5th Annual Learning for Dynamics and Control Conference, L4DC 2023. - : ML Research Press. ; , s. 1297-1307
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Konferensbidrag (refereegranskat)abstract
- The ongoing development of telecommunication systems like 5G has led to an increase in demand of well calibrated base transceiver station (BTS) components. A pivotal component of every BTS is cavity filters, which provide a sharp frequency characteristic to select a particular band of interest and reject the rest. Unfortunately, their characteristics in combination with manufacturing tolerances make them difficult for mass production and often lead to costly manual post-production fine tuning. To address this, numerous approaches have been proposed to automate the tuning process. One particularly promising one, that has emerged in the past few years, is to use model free reinforcement learning (MFRL); however, the agents are not sample efficient. This poses a serious bottleneck, as utilising complex simulators or training with real filters is prohibitively time demanding. This work advocates for the usage of model based reinforcement learning (MBRL) and showcases how its utilisation can significantly decrease sample complexity, while maintaining similar levels of success rate. More specifically, we propose an improvement over a state-of-the-art (SoTA) MBRL algorithm, namely the Dreamer algorithm. This improvement can serve as a template for applications in other similar, high-dimensional non-image data problems. We carry experiments on two complex filter types, and show that our novel modification on the Dreamer architecture reduces sample complexity by a factor of 4 and 10, respectively. Our findings pioneer the usage of MBRL which paves the way for utilising more precise and accurate simulators which was previously prohibitively time demanding.
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| 22. |
- Pallin, Martin, et al.
(författare)
-
A Decentralized Asynchronous Collaborative Genetic Algorithm for Heterogeneous Multi-agent Search and Rescue Problems
- 2021
-
Ingår i: 2021 IEEE International Symposium on Safety, Security, and Rescue Robotics, SSRR 2021. - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 1-8
-
Konferensbidrag (refereegranskat)abstract
- In this paper we propose a version of the Genetic Algorithm (GA) for combined task assignment and path planning that is highly decentralized in the sense that each agent only knows its own capabilities and data, and a set of so-called handover values communicated to it from the other agents over an unreliable low bandwidth communication channel. These handover values are used in combination with a local GA involving no other agents, to decide what tasks to execute, and what tasks to leave to others. We compare the performance of our approach to a centralized version of GA, and a partly decentralized version of GA where computations are local, but all agents need complete information regarding all other agents, including position, range, battery, and local obstacle maps. We compare solution performance as well as messages sent for the three algorithms, and conclude that the proposed algorithms has a small decrease in performance, but a significant decrease in required communication. We compare the performance of our approach to a centralized version of GA, and a partly decentralized version of GA where computations are local, but all agents need complete information regarding all other agents, including position, range, battery, and local obstacle maps. We compare solution performance as well as messages sent for the three algorithms, and conclude that the proposed algorithms has a small decrease in performance, but a significant decrease in required communication. We compare solution performance as well as messages sent for the three algorithms, and conclude that the proposed algorithms has a small decrease in performance, but a significant decrease in required communication.
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| 23. |
- Pallin, Martin, et al.
(författare)
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Formulation and Solution of the Multi-agent Concurrent Search and Rescue Problem
- 2021
-
Ingår i: IEEE International Symposium on Safety, Security, and Rescue Robotics, SSRR 2021. - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 27-33
-
Konferensbidrag (refereegranskat)abstract
- In this paper we formulate and solve the concurrent multi-agent search and rescue problem (C-SARP), where a multi-agent system is to concurrently search an area and assist the victims found during the search. It is widely believed that a UAV-system can help saving lives by locating and assisting victims over large inaccessible areas in the initial stages after a disaster, such as an earthquake, flood, or plane crash. In such a scenario, a natural objective is to minimize the loss of lives. Therefore, two types of uncertainties needs to be taken into account, the uncertainty in position of the victims, and the uncertainty in health over time. It is rational to start looking where victims are most likely to be found, such as the reported position of a victim in a life boat with access to a radio, but it is also rational to start looking where loss of lives is most likely to occur, such as the uncertain position of victims swimming in cold water. We show that the proposed C-SARP is NP-hard, and that the two elements of search and rescue should not be decoupled, making C-SARP substantially different from previously studied multi agent problems, including coverage, multi agent travelling salesmen problems and earlier studies of decoupled search and rescue. Finally, we provide an experimental comparison between the most promising algorithms used in the literature to address similar problems, and find that the solutions to the C-SARP reproduce the trajectories recommended in search and rescue manuals for simple problems, but outperform those trajectories in terms of expected survivability for more complex scenarios.
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| 24. |
- Parasuraman, Ramviyas, et al.
(författare)
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Kalman Filter Based Spatial Prediction of Wireless Connectivity for Autonomous Robots and Connected Vehicles
- 2018
-
Ingår i: 2018 IEEE 88TH VEHICULAR TECHNOLOGY CONFERENCE (VTC-FALL). - : IEEE. - 9781538663585
-
Konferensbidrag (refereegranskat)abstract
- This paper proposes a new Kalman filter based online framework to estimate the spatial wireless connectivity in terms of received signal strength (RSS), which is composed of path loss and the shadow fading variance of a wireless channel in autonomous vehicles. The path loss is estimated using a localized least squares method and the shadowing effect is predicted with an empirical (exponential) variogram. A discrete Kalman Filter is used to fuse these two models into a state space formulation. The approach is unique in a sense that it is online and does not require the exact source location to be known apriori. We evaluated the method using real-world measurements dataset from both indoors and outdoor environments. The results show significant performance improvements compared to state-of-the-art methods using Gaussian processes or Kriging interpolation algorithms. We are able to achieve a mean prediction accuracy of up to 96% for predicting RSS as far as 20 meters ahead in the robot's trajectory.
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| 25. |
- Parasuraman, Ramviyas, et al.
(författare)
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Rapid prediction of network quality in mobile robots
- 2023
-
Ingår i: Ad hoc networks. - : Elsevier BV. - 1570-8705 .- 1570-8713. ; 138
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Tidskriftsartikel (refereegranskat)abstract
- Mobile robots rely on wireless networks for sharing sensor data from remote missions. The robot's spatial network quality will vary considerably across a given mission environment and network access point (AP) location, which are often unknown apriori. Therefore, predicting these spatial variations becomes essential and challenging, especially in dynamic and unstructured environments. To address this challenge, we propose an online algorithm to predict wireless connection quality measured through the well-exploited Radio Signal Strength (RSS) metric in the future positions along a mobile robot's trajectory. We assume no knowledge of the environment or AP positions other than robot odometry and RSS measurements at the previous trajectory points. We propose a discrete Kalman filter-based solution considering path loss and shadowing effects. The algorithm is evaluated with unique real-world datasets in indoor, outdoor, and underground data showing prediction accuracy of up to 96%, revealing significant performance improvements over conventional approaches, including Gaussian Processes Regression. Having such accurate predictions will help the robot plan its trajectory and task operations in a communication-aware manner ensuring mission success. Further, we extensively analyze the approach regarding the impacts of localization error, source location, mobility, antenna type, and connection failures on prediction accuracy, providing novel perspectives and observations for performance evaluation.
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| 26. |
- Robinson, John, et al.
(författare)
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On the use of gradual dense-sparse discretizations in receding horizon control
- 2014
-
Ingår i: Optimal control applications & methods. - : Wiley-Blackwell. - 0143-2087 .- 1099-1514. ; 35:3, s. 253-270
-
Tidskriftsartikel (refereegranskat)abstract
- A key factor to success in implementations of real time optimal control, such as receding horizon control (RHC), is making efficient use of computational resources. The main trade-off is then between efficiency and accuracy of each RHC iteration, and the resulting overall optimality properties of the concatenated iterations, that is, how closely this represents a solution to the underlying infinite time optimal control problem (OCP). Both these issues can be addressed by adapting the RHC solution strategy to the expected form of the solution. Using gradual dense-sparse (GDS) node distributions in direct transcription formulations of the finite time OCP solved in each RHC iteration is a way of adapting the node distribution of this OCP to the fact that it is actually part of an RHC scheme. We have previously argued that this is reasonable, because the near future plan must be implemented now, but the far future plan can and will be revised later. In this paper, we investigate RHC applications where the asymptotic qualitative behavior of the OCP solution can be analyzed in advance. For some classes of systems, explicit exponential convergence rates of the solutions can be computed. We establish such convergence rates for a class of control affine nonlinear systems with a locally quadratic cost and propose to use versions of GDS node distributions for such systems because they will (eventually) be better adapted to the form of the solution. The advantages of the GDS approach in such settings is illustrated with simulations.
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| 27. |
- Scukins, Edvards, et al.
(författare)
-
A Data-driven Method for Estimating Formation Flexibility in Beyond-Visual-Range Air Combat
- 2024
-
Ingår i: 2024 International Conference on Unmanned Aircraft Systems (ICUAS). - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 241-247
-
Konferensbidrag (refereegranskat)abstract
- Tactical decisions in air combat are typically evaluated using experience as a basis. Pilots undergo frequent training in various air combat processes to enhance their combat proficiency and evaluation skills. Having the Situational Awareness (SA) necessary to evaluate the effects of multiple missile threats can often be challenging. This study provides a new method for calculating an aircraft fleet's maneuver flexibility in a Beyond-Visual-Range (BVR) setting. Sustaining a high degree of flexibility is necessary to adapt to unforeseen circumstances in BVR air combat. To do that, we employ Deep Neural Networks (DNN) to capture the result of a highperformance aircraft model in the presence of adversarial BVR missiles. We then modify our approach to calculate the aircraft's maneuverability concerning an opposing fleet, looking at the advantages and disadvantages of several flight formations. Finally, we consider the anticipated threat from an incoming opponent formation and optimize the counter-formation. This methodology offers a more sophisticated comprehension of aircraft maneuver flexibility within a BVR framework and aids in developing flexible and efficient decision-making techniques for air combat.
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| 28. |
- Scukins, Edvards, et al.
(författare)
-
Classical Formation Patterns and Flanking Strategies as a Result of Utility Maximization
- 2019
-
Ingår i: IEEE Control Systems Letters. - : IEEE. - 2475-1456. ; 3:2, s. 422-427
-
Tidskriftsartikel (refereegranskat)abstract
- In this paper, we show how classical tactical forma- tion patterns and flanking strategies, such as the line formation and the enveloping maneuver, can be seen as the result of maximizing a natural formation utility.The problem of automatic formation keeping is extremely well studied within the areas of control and robotics, but the reasons for choosing a particular formation shape and position is much less so.By analyzing a situation with two adversarial teams of agents facing each other, we show that natural assumptions regarding the target selection of the agents and decreasing weapon efficiency over distance, can be used to optimize a measure of utility over agent positions. This optimization in turn results in formations and positions that are very similar to the ones being used in practice. We present both analytical results for simple examples as well as numerical results for more complex situations.
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| 29. |
- Scukins, Edvards, et al.
(författare)
-
Deep Learning Based Situation Awareness for Multiple Missiles Evasion
- 2024
-
Ingår i: 2024 International Conference on Unmanned Aircraft Systems, ICUAS 2024. - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 1446-1452
-
Konferensbidrag (refereegranskat)abstract
- As the effective range of air-to-air missiles increases, it becomes harder for pilots and Unmanned aerial vehicle (UAV) operators to maintain the Situational Awareness (SA) needed to keep their aircraft safe. In this work, we propose a decision support tool to help pilots in Beyond Visual Range (BVR) air combat scenarios assess the risks of different options and make decisions based on those. Building upon earlier research that primarily addressed the threat of a single missile, we extend these ideas to encompass the complex scenario of multiple missile threats. The proposed method uses Deep Neural Networks (DNN) to learn from high-fidelity simulations and provide the pilots with an outcome estimate for a set of different strategies. Our results demonstrate that the proposed system can manage multiple incoming missiles, evaluate a family of options, and recommend the least risky course of action while accounting for all incoming air-to-air threats.
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| 30. |
- Scukins, Edvards, et al.
(författare)
-
Enhancing Situation Awareness in Beyond Visual Range Air Combat with Reinforcement Learning-based Decision Support
- 2023
-
Ingår i: 2023 International Conference on Unmanned Aircraft Systems, ICUAS 2023. - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 56-62
-
Konferensbidrag (refereegranskat)abstract
- Military aircraft pilots need to adjust to a constantly changing battlefield. A system that aids in understanding challenging combat circumstances and suggests appropriate responses can considerably improve the effectiveness of pilots. In this paper, we provide a Reinforcement Learning (RL) based system that acts as an aid in determining if an afterburner should be turned on to escape an incoming air-to-air missile. An afterburner is a component of a jet engine that increases thrust at the expense of exceptionally high fuel consumption. Thus it provides a short-term advantage, at the cost of a longterm disadvantage, in terms of reduced mission time. Helping to choose when to use the afterburner may significantly lengthen the flight duration, allowing aircraft to support friendly aircraft for longer and suffer fewer friendly fatalities due to this extended ability to provide support. We propose an RL-based risk estimation approach to help determine whether additional thrust is required to escape an incoming missile and study the benefits of thrust-aided evasive maneuvers. The suggested technique gives pilots a risk estimate for the scenario and a recommended course of action. We create an environment in which a pilot must decide whether or not to activate additional thrust to achieve the intended aim at a potentially high fuel consumption cost. Additionally, we investigate various trade-offs of the generated evasive maneuver policies.
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| 31. |
- Scukins, Edvards, et al.
(författare)
-
Monte Carlo Tree Search and Convex Optimization for Decision Support in Beyond-Visual-Range Air Combat
- 2023
-
Ingår i: 2023 International Conference on Unmanned Aircraft Systems, ICUAS 2023. - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 48-55
-
Konferensbidrag (refereegranskat)abstract
- Air combat is a high-risk activity where pilots must be aware of the surrounding situation to outperform the opposing team. The chances of beating the opposing team improve when the pilots have superior situation awareness, thus allowing them to act before the opposing team can do counteractions. In a highly dynamic environment, such as air combat, it can be difficult for pilots to track all adversarial units and their capabilities. In this work, we propose a combination of Monte Carlo Tree Search (MCTS) and Convex optimization to help pilots analyze the situation and be aware of any potential risks associated with missile guidance in Beyond Visual Range air combat. Our process uses MCTS to assess the best action from an opposing aircraft perspective. At the same time, the convex optimization problem searches available aircraft trajectories that enable missile guidance in relation to the opponent's potential actions. The proposed system is intended to support human decisions made by a pilot inside the aircraft or by a remote pilot operating an unmanned aerial system (UAS).
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| 32. |
- Scukins, Edvards, et al.
(författare)
-
Using Reinforcement Learning to Create Control Barrier Functions for Explicit Risk Mitigation in Adversarial Environments
- 2021
-
Ingår i: 2021 IEEE International Conference on Robotics and Automation (ICRA). - : IEEE Robotics and Automation Society.
-
Konferensbidrag (refereegranskat)abstract
- Air Combat is a high-risk activity carried out by trained professionals operating sophisticated equipment. During this activity, a number of trade-offs have to be made, such as the balance between risk and efficiency. A policy that minimizes risk could have very low efficiency, and one that maximizes efficiency may involve very high risk.In this study, we use Reinforcement Learning (RL) to create Control Barrier Functions (CBF) that captures the current risk, in terms of worst-case future separation between the aircraft and an enemy missile.CBFs are usually designed manually as closed-form expressions, but for a complex system such as a guided missile, this is not possible. Instead, we solve an RL problem using high fidelity simulation models to find value functions with CBF properties, that can then be used to guarantee safety in real air combat situations. We also provide a theoretical analysis of what family of RL problems result in value functions that can be used as CBFs in this way.The proposed approach allows the pilot in an air combat scenario to set the exposure level deemed acceptable and continuously monitor the risk related to his/her own safety. Given input regarding acceptable risk, the system limits the choices of the pilot to those that guarantee future satisfaction of the provided bound.
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| 33. |
- Sprague, Christopher, et al.
(författare)
-
Adding Neural Network Controllers to Behavior Trees without Destroying Performance Guarantees
- 2022
-
Ingår i: The 61th IEEE Conference on Decision and Control (CDC 2022). - : Institute of Electrical and Electronics Engineers (IEEE).
-
Konferensbidrag (refereegranskat)abstract
- In this paper, we show how Behavior Trees that have performance guarantees, in terms of safety and goal convergence, can be extended with components that were designed using machine learning, without destroying those performance guarantees. Machine learning approaches such as reinforcement learning or learning from demonstration can be very appealing to AI designers that want efficient and realistic behaviors in their agents. However, those algorithms seldom provide guarantees for solving the given task in all different situations while keeping the agent safe. Instead, such guarantees are often easier to find for manually designed model-based approaches. In this paper we exploit the modularity of behavior trees to extend a given design with an efficient, but possibly unreliable, machine learning component in a way that preserves the guarantees. The approach is illustrated with an inverted pendulum example.
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| 34. |
- Sprague, Christopher, et al.
(författare)
-
An Extended Convergence Result for Behavior Tree Controllers
-
Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Behavior trees (BTs) is an optimally modular framework to assemble hierarchical hybrid control policies from a set of low-level control policies using a tree structure. Many robotic tasks are naturally decomposed into a hierarchy of control tasks, and modularity is a well-known tool for handling complexity, therefor behavior trees have garnered widespread usage in the robotics community. In this paper, we study the convergence of BTs, in the sense of reaching a desired part of the state space. Earlier results on BT convergence were often tailored to specific families of BTs, created using different design principles. The results of this paper generalize the earlier results, and also include new cases of cyclic switching not covered in the literature.
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| 35. |
- Sprague, Christopher, et al.
(författare)
-
Continuous-Time Behavior Trees as Discontinuous Dynamical Systems
- 2022
-
Ingår i: IEEE Control Systems Letters. - : Institute of Electrical and Electronics Engineers (IEEE). - 2475-1456. ; 6, s. 1891-1896
-
Tidskriftsartikel (refereegranskat)abstract
- Behavior trees represent a hierarchical and modular way of combining several low-level control policies into a high-level task-switching policy. Hybrid dynamical systems can also be seen in terms of task switching between different policies, and therefore several comparisons between behavior trees and hybrid dynamical systems have been made, but only informally, and only in discrete time. A formal continuous-time formulation of behavior trees has been lacking. Additionally, convergence analyses of specific classes of behavior tree designs have been made, but not for general designs. In this letter, we provide the first continuous-time formulation of behavior trees, show that they can be seen as discontinuous dynamical systems (a subclass of hybrid dynamical systems), which enables the application of existence and uniqueness results to behavior trees, and finally, provide sufficient conditions under which such systems will converge to a desired region of the state space for general designs. With these results, a large body of results on continuous-time dynamical systems can be brought to use when designing behavior tree controllers.
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| 36. |
- Sprague, Christopher
(författare)
-
Efficient and Trustworthy Artificial Intelligence for Critical Robotic Systems
- 2022
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Critical robotic systems are systems whose functioning is critical to both ensuring the accomplishment of a given mission and preventing the endangerment of life and the surrounding environment. These critical aspects can be formally captured by convergence, in the sense that the system's state goes to a desired region of the statespace, and safety, in the sense that the system's state avoids unsafe regions of the statespace. Data-driven control policies, found through e.g. imitation learning or reinforcement learning, can outperform model-based methods in achieving convergence and safety efficiently; however, they often only do so by encouraging them, thus, they can be difficult to trust. Model-based control policies, on the other hand, are often well-suited to admitting formal guarantees of convergence and safety, thus they are often easier to trust. The main question asked in this thesis is: how can we compose data-driven and model-based control policies together to encourage efficiency while, at the same time, formally guaranteeing convergence and safety?We answer this question with behaviour trees, a framework to represent hybrid control systems in a modular way. We present the first formal definition of behaviour trees as a hybrid system and present the conditions under which the execution of any behaviour tree as a hybrid control system will formally guarantee convergence and safety. Moreover, we present the conditions under which such formal guarantees can be maintained when including unguaranteed data-driven control policies, such as those coming from imitation learning or reinforcement learning. We also present an approach to synthesise such data-driven control policies in such a way that they encourage convergence and safety by adapting to unforeseen events. Alongside the above, we also explore an ancillary aspect of robot autonomy by improving the efficiency of simultaneous localisation and mapping through imitation learning. Lastly, we validate the advantages of behaviour trees' modularity in a real-world autonomous underwater vehicle's control system, and argue that this modularity contributes to efficiency, in terms of ease of use, and trust, in terms of facilitating human understanding.
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| 37. |
- Sprague, Christopher, et al.
(författare)
-
Improving the Modularity of AUV Control Systems using Behaviour Trees
- 2018
-
Ingår i: AUV 2018 - 2018 IEEE/OES Autonomous Underwater Vehicle Workshop, Proceedings. - : Institute of Electrical and Electronics Engineers Inc.. - 9781728102535
-
Konferensbidrag (refereegranskat)abstract
- In this paper, we show how behaviour trees (BTs) can be used to design modular, versatile, and robust control architectures for mission-critical systems. In particular, we show this in the context of autonomous underwater vehicles (AUVs). Robustness, in terms of system safety, is important since manual recovery of AUVs is often extremely difficult. Further more, versatility is important to be able to execute many different kinds of missions. Finally, modularity is needed to achieve a combination of robustness and versatility, as the complexity of a versatile systems needs to be encapsulated in modules, in order to create a simple overall structure enabling robustness analysis. The proposed design is illustrated using a typical AUV mission.
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| 38. |
- Sprague, Christopher, et al.
(författare)
-
Learning Dynamic-Objective Policies from a Class of Optimal Trajectories
- 2020
-
Ingår i: Proceedings of the IEEE Conference on Decision and Control. - : Institute of Electrical and Electronics Engineers Inc.. ; , s. 597-602
-
Konferensbidrag (refereegranskat)abstract
- Optimal state-feedback controllers, capable of changing between different objective functions, are advantageous to systems in which unexpected situations may arise. However, synthesising such controllers, even for a single objective, is a demanding process. In this paper, we present a novel and straightforward approach to synthesising these policies through a combination of trajectory optimisation, homotopy continuation, and imitation learning. We use numerical continuation to efficiently generate optimal demonstrations across several objectives and boundary conditions, and use these to train our policies. Additionally, we demonstrate the ability of our policies to effectively learn families of optimal state- feedback controllers, which can be used to change objective functions online. We illustrate this approach across two trajectory optimisation problems, an inverted pendulum swingup and a spacecraft orbit transfer, and show that the synthesised policies, when evaluated in simulation, produce trajectories that are near-optimal. These results indicate the benefit of trajectory optimisation and homotopy continuation to the synthesis of controllers in dynamic-objective contexts.
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| 39. |
- Sprague, Christopher, et al.
(författare)
-
Learning How to Learn Bathymetry
- 2020
-
Ingår i: 2020 IEEE/OES Autonomous Underwater Vehicles Symposium, AUV 2020. - : Institute of Electrical and Electronics Engineers Inc..
-
Konferensbidrag (refereegranskat)abstract
- In this work, we investigate using reinforcement learning (RL) to learn controllers that generate continuous trajectories that minimise the uncertainty of a bathymetric model of a given environment, whilst respecting time constraints.
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| 40. |
- Tardioli, Danilo, et al.
(författare)
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Pound : A multi-master ROS node for reducing delay and jitter in wireless multi-robot networks
- 2019
-
Ingår i: Robotics and Autonomous Systems. - : Elsevier. - 0921-8890 .- 1872-793X. ; 111, s. 73-87
-
Tidskriftsartikel (refereegranskat)abstract
- The Robot Operating System (ROS) is a popular and widely used software framework for building robotics systems. With the growth of its popularity, it has started to be used in multi-robot systems as well. However, the TCP connections that the platform relies on for connecting the so-called ROS nodes presents several issues regarding limited-bandwidth, delays, and jitter, when used in wireless multi-hop networks. In this paper, we present a thorough analysis of the problem and propose a new ROS node called Pound to improve the wireless communication performance by reducing delay and jitter in data exchanges, especially in multi-hop networks. Pound allows the use of multiple ROS masters (roscores), features data compression, and importantly, introduces a priority scheme that allows favoring more important flows over less important ones. We compare Pound to the state-of-the-art solutions through extensive experiments and show that it performs equally well, or better in all the test cases, including a control-over-network example.
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| 41. |
- Ögren, Petter, 1974-, et al.
(författare)
-
A Multi Objective Control Approach to Online Dual Arm Manipulation
- 2012
-
Ingår i: Robot Control. - : International Federation of Automatic Control. - 9783902823113 ; , s. 747-752
-
Konferensbidrag (refereegranskat)abstract
- In this paper, we propose a new way to exploit the redundancy of dual arm mobile manipulators when performing inherently bi-manual tasks using online controllers. Bi-manual tasks are tasks that require motion of both arms in order to be carried out efficiently, such as holding and cleaning an object, or moving an object from one hand to the other. These tasks are often associated with several constraints, such as singularity- and collision avoidance, but also a high degree of redundancy, as the relative positions of the two grippers is far more important than the absolute positions, when for example handing an object from one arm to the other. By applying a modular multi objective control framework, inspired by earlier work on sub-task control, we exploit this redundancy to form a subset of the joint space that is feasible, i.e. not violating any of the constraints. Earlier approacher added the additional tasks in terms of equality constraints, thereby reducing the dimension of the feasible subset until it was a single point. Here however, we add the additional tasks in terms of inequalities, removing parts of the feasible set rather than collapsing its dimensionality. Thus, we are able to handle an arbitrary number of constraints, instead of a number corresponding to the dimension of the feasible set (degree of redundancy). Finally, inside the feasible set we choose controls stay in the set, while simultaneously minimizing some given objective. The proposed approach is illustrated by several simulation examples.
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| 42. |
- Ögren, Petter, 1974-, et al.
(författare)
-
Behavior Trees in Robot Control Systems
- 2022
-
Ingår i: Annual Review of Control, Robotics, and Autonomous Systems. - : Annual Reviews. - 2573-5144 .- 2573-5144. ; 5:1, s. 81-107
-
Tidskriftsartikel (refereegranskat)abstract
- In this article, we provide a control-theoretic perspective on the research area of behavior trees in robotics. The key idea underlying behavior trees is to make use of modularity, hierarchies, and feedback in order to handle the complexity of a versatile robot control system. Modularity is a well-known tool to handle software complexity by enabling the development, debugging, and extension of separate modules without detailed knowledge of the entire system. A hierarchy of such modules is natural, since robot tasks can often be decomposed into a hierarchy of subtasks. Finally, feedback control is a fundamental tool for handling uncertainties and disturbances in any low-level control system, but in order to enable feedback control on the higher level, where one module decides what submodule to execute, information regarding the progress and applicability of each submodule needs to be shared in the module interfaces. We describe how these three concepts can be used in theoretical analysis, practical design, and extensions and combinations with other ideas from control theory and robotics.
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| 43. |
- Ögren, Petter, 1974-, et al.
(författare)
-
Behavior Trees in Robotics and AI: An Introduction
- 2018. - First
-
Bok (refereegranskat)abstract
- Behavior Trees (BTs) provide a way to structure the behavior of an artificial agent such as a robot or a non-player character in a computer game. Traditional design methods, such as finite state machines, are known to produce brittle behaviors when complexity increases, making it very hard to add features without breaking existing functionality. BTs were created to address this very problem, and enables the creation of systems that are both modular and reactive. Behavior Trees in Robotics and AI: An Introduction provides a broad introduction as well as an in-depth exploration of the topic, and is the first comprehensive book on the use of BTs.
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| 44. |
- Ögren, Petter, 1974-
(författare)
-
Convergence Analysis of Hybrid Control Systems in the Form of Backward Chained Behavior Trees
- 2020
-
Ingår i: IEEE Robotics and Automation Letters. - : IEEE Robotics and Automation Society. - 2377-3766.
-
Tidskriftsartikel (refereegranskat)abstract
- A robot control system is often composed of a set of low level continuous controllers and a switching policy that decides which of those continuous controllers to apply at each time instant. The switching policy can be either a Finite State Machine (FSM), a Behavior Tree (BT) or some other structure. In previous work we have shown how to create BTs using a backward chained approach that results in a reactive goal directed policy. This policy can be thought of as providing disturbance rejection at the task level in the sense that if a disturbance changes the state in such a way that the currently running continuous controller cannot handle it, the policy will switch to the appropriate continuous controller. In this letter we show how to provide convergence guarantees for such policies.
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| 45. |
|
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| 46. |
- Ögren, Petter, 1974-, et al.
(författare)
-
Creating Trustworthy AI for UAS using Labeled Backchained Behavior Trees
- 2023
-
Ingår i: 2023 International Conference on Unmanned Aircraft Systems, ICUAS 2023. - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 1029-1036
-
Konferensbidrag (refereegranskat)abstract
- Unmanned Aerial Systems (UAS) have the potential to provide cost effective solutions to many problems, but their control systems need to be safe and trustworthy in order to realize this potential. In this paper we show how behavior trees (BTs), created using backward chaining and using a particular way of labelling subtrees, can be used to meet the requirements of trustworthy autonomy described in a US air force (USAF) report. Behavior Trees represent a modular, reactive and transparent way of structuring a control system that is receiving increasing interest in the UAS community. While their safety and efficiency have been investigated in prior research, their connection to trustworthy autonomy has not been explored. A set of guidelines for trustworthy autonomy, taken from a USAF report, include items such as: being similar to how humans parse problems, being able to explain its reasoning in a concise way, and being able to be visualized at different levels of resolution. We propose a new way of deriving explanations that conform to these guidelines, using a particular labeling of subtrees in the BT combined with a structured design methodology called backward chaining. The proposed approach is illustrated in a detailed example.
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| 47. |
- Ögren, Petter, 1974-, et al.
(författare)
-
Design and implementation of a new teleoperation control mode for differential drive UGVs
- 2014
-
Ingår i: Autonomous Robots. - : Springer Science and Business Media LLC. - 0929-5593 .- 1573-7527. ; 37:1, s. 71-79
-
Tidskriftsartikel (refereegranskat)abstract
- In this paper, we propose and implement a new control mode for teleoperated unmanned ground vehicles (UGVs), that exploits the similarities between computer games and teleoperation robotics. Today, all teleoperated differential drive UGVs use a control mode called Tank Control, in which the UGV chassis and the pan tilt camera are controlled separately. This control mode was also the dominating choice when the computer game genre First Person Shooter (FPS) first appeared. However, the hugely successful FPS genre, including titles such as Doom, Half Life and Call of Duty, now uses a much more intuitive control mode, Free Look Control (FLC), in which rotation and translation of the character are decoupled, and controlled separately. The main contribution of this paper is that we replace Tank Control with FLC in a real UGV. Using feedback linearization, the orientation of the UGV chassis is abstracted away, and the orientation and translation of the camera are decoupled, enabling the operator to use FLC when controlling the UGV. This decoupling is then experimentally verified. The developments in the gaming community indicates that FLC is more intuitive than Tank Control and reduces the well known situational awareness problem. It furthermore reduces the need for operator training, since literary millions of future operators have already spent hundreds of hours using the interface.
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| 48. |
- Ögren, Petter, 1974-
(författare)
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Formations and Obstacle Avoidance in Mobile Robot Control
- 2003
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This thesis consists of four independent papers concerningthe control of mobile robots in the context of obstacleavoidance and formation keeping. The first paper describes a new theoreticallyv erifiableapproach to obstacle avoidance. It merges the ideas of twoprevious methods, with complementaryprop erties, byusing acombined control Lyapunov function (CLF) and model predictivecontrol (MPC) framework. The second paper investigates the problem of moving a fixedformation of vehicles through a partiallykno wn environmentwith obstacles. Using an input to state (ISS) formulation theconcept of configuration space obstacles is generalized toleader follower formations. This generalization then makes itpossible to convert the problem into a standard single vehicleobstacle avoidance problem, such as the one considered in thefirst paper. The properties of goal convergence and safetyth uscarries over to the formation obstacle avoidance case. In the third paper, coordination along trajectories of anonhomogenuos set of vehicles is considered. Byusing a controlLyapunov function approach, properties such as boundedformation error and finite completion time is shown. Finally, the fourth paper applies a generalized version ofthe control in the third paper to translate,rotate and expanda formation. It is furthermore shown how a partial decouplingof formation keeping and formation mission can be achieved. Theapproach is then applied to a scenario of underwater vehiclesclimbing gradients in search for specific thermal/biologicalregions of interest. The sensor data fusion problem fordifferent formation configurations is investigated and anoptimal formation geometryis proposed. Keywords:Mobile Robots, Robot Control, ObstacleAvoidance, Multirobot System, Formation Control, NavigationFunction, Lyapunov Function, Model Predictive Control, RecedingHorizon Control, Gradient Climbing, Gradient Estimation.
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| 49. |
- Ögren, Petter, 1974-
(författare)
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Increasing Modularity of UAV Control Systems using Computer Game Behavior Trees
- 2012
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Ingår i: AIAA Guidance, Navigation, and Control Conference 2012. - 9781600869389
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Konferensbidrag (refereegranskat)abstract
- In this paper, we argue that the modularity, reusability and complexity of Unmanned Aerial Vehicle (UAV) guidance and control systems might be improved by using a Behavior Tree (BT) architecture. BTs are a particular kind of Hybrid Dynamical Systems (HDS), where the state transitions of the HDS are implicitly encoded in a tree structure, instead of explicitly stated in transition maps. In the gaming industry, BTs have gained a lot of interest, and are now replacing HDS in the control architecture of many automated in-game opponents. Below, we explore the relationship between HDS and BTs. We show that any HDS can be written as a BT and that many common UAV control constructs are quite naturally formulated as BTs. Finally, we discuss the positive implications of making the above mentioned state transitions implicit in the BTs.
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| 50. |
- Özkahraman, Özer, 1992-, et al.
(författare)
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Collaborative Navigation-Aware Coverage in Feature-Poor Environments
- 2022
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Ingår i: International Conference on Intelligent Robots and Systems (IROS), 2022.
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Konferensbidrag (refereegranskat)abstract
- Multi agent coverage and robot navigation are two very important research fields within robotics. However, their intersection has received limited attention. In multi agent coverage, perfect navigation is often assumed, and in robot navigation, the focus is often to minimize the localization error with the aid of stationary features from the environment.The need for integration of the two becomes clear in environments with very sparse features or landmarks, for example when a group of Autonomous Underwater Vehicles (AUVs) are to search a uniform seafloor for mines or other dangerous objects.In such environments, localization systems are often deprived of detectable features to use that could increase their accuracy.In this paper we propose an algorithm for doing navigation aware multi agent coverage in areas with no landmarks.Instead of using identical lawn mower patterns, we propose to mirror every other pattern to enable the agents to meet up and makeinter-agent measurements and share information regularly. This improves performance in two ways,global drift in relation to the area to be covered is reduced, and local coverage gaps between adjacent patterns are reduced.Further, we show that this can be accomplished within the constraints of very limited sensing, computing and communication resources that most AUVs have available.The effectiveness of our method is shown through statistically significant simulated experiments.
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