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1.	Almeida, Diogo, 1991-, et al. (author) Team KTH’s Picking Solution for the Amazon Picking Challenge 2016 2017 In: Warehouse Picking Automation Workshop 2017. Conference paper (pop. science, debate, etc.)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.
2.	Almeida, Diogo, 1991-, et al. (author) Team KTH’s Picking Solution for the Amazon Picking Challenge 2016 2020 In: Advances on Robotic Item Picking: Applications in Warehousing and E-Commerce Fulfillment. - Cham : Springer Nature. ; , s. 53-62 Book chapter (other academic/artistic)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.
3.	Andersson, Klas, 1968- (author) Improving Fixed Wing UAV Endurance, by Cooperative Autonomous Soaring 2021 Doctoral thesis (other academic/artistic)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.
4.	Andersson, Olov, 1979- (author) Methods for Scalable and Safe Robot Learning 2017 Licentiate thesis (other academic/artistic)abstract Robots are increasingly expected to go beyond controlled environments in laboratories and factories, to enter real-world public spaces and homes. However, robot behavior is still usually engineered for narrowly defined scenarios. To manually encode robot behavior that works within complex real world environments, such as busy work places or cluttered homes, can be a daunting task. In addition, such robots may require a high degree of autonomy to be practical, which imposes stringent requirements on safety and robustness. \setlength{\parindent}{2em}\setlength{\parskip}{0em}The aim of this thesis is to examine methods for automatically learning safe robot behavior, lowering the costs of synthesizing behavior for complex real-world situations. To avoid task-specific assumptions, we approach this from a data-driven machine learning perspective. The strength of machine learning is its generality, given sufficient data it can learn to approximate any task. However, being embodied agents in the real-world, robots pose a number of difficulties for machine learning. These include real-time requirements with limited computational resources, the cost and effort of operating and collecting data with real robots, as well as safety issues for both the robot and human bystanders.While machine learning is general by nature, overcoming the difficulties with real-world robots outlined above remains a challenge. In this thesis we look for a middle ground on robot learning, leveraging the strengths of both data-driven machine learning, as well as engineering techniques from robotics and control. This includes combing data-driven world models with fast techniques for planning motions under safety constraints, using machine learning to generalize such techniques to problems with high uncertainty, as well as using machine learning to find computationally efficient approximations for use on small embedded systems.We demonstrate such behavior synthesis techniques with real robots, solving a class of difficult dynamic collision avoidance problems under uncertainty, such as induced by the presence of humans without prior coordination. Initially using online planning offloaded to a desktop CPU, and ultimately as a deep neural network policy embedded on board a 7 quadcopter.
5.	Anisi, David A., 1977-, et al. (author) Algorithms for the connectivity constrained unmanned ground vehicle surveillance problem 2009 In: European Control Conference (ECC). - Budapest, Hungary : EUCA. Conference paper (peer-reviewed)abstract The Connectivity Constrained UGV Surveillance Problem (CUSP) considered in this paper is the following. Given a set of surveillance UGVs and a user defined area to be covered, find waypoint-paths such that; 1) the area is completely surveyed, 2) the time for performing the search is minimized and 3) the induced information graph is kept recurrently connected. It has previously been shown that the CUSP is NP-hard. This paper presents four different heuristic algorithms for solving the CUSP, namely, the Token Station Algorithm, the Stacking Algorithm, the Visibility Graph Algorithm and the Connectivity Primitive Algorithm. These algorithms are then compared by means of Monte Carlo simulations. The conclusions drawn are that the Token Station Algorithm provides the most optimal solutions, the Stacking Algorithm has the lowest computational complexity, while the Connectivity Primitive Algorithm provides the best trade-off between optimality and computational complexity for larger problem instances.
6.	Anisi, David A., 1977-, et al. (author) Communication constrained multi-UGV surveillance 2008 In: IFAC World Congress. - Seoul, Korea. Conference paper (peer-reviewed)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.
7.	Anisi, David A., et al. (author) Cooperative Minimum Time Surveillance With Multiple Ground Vehicles 2010 In: IEEE Transactions on Automatic Control. - 0018-9286 .- 1558-2523. ; 55:12, s. 2679-2691 Journal article (peer-reviewed)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.
8.	Anisi, David A., et al. (author) Cooperative Surveillance Missions with Multiple Unmanned Ground Vehicles (UGVs) 2008 In: 47TH IEEE CONFERENCE ON DECISION AND CONTROL, 2008 (CDC 2008). - 9781424431243 ; , s. 2444-2449 Conference paper (peer-reviewed)abstract This paper proposes an optimization based approach to multi-UGV surveillance. In particular, we formulate both the minimum time- and connectivity constrained surveillance problems, show NP-hardness of them and propose decomposition techniques that allow us to solve them efficiently in an algorithmic manner. The minimum time formulation 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 sensor's field of view are assumed to be occluded by the obstacles and limited by a maximal sensor range. The connectivity constrained formulation extends the first by additionally requiring that the information graph induced by the sensors is connected at the time instants when the UGVs stop to perform the surveillance task. The second formulation is relevant to situation when mutual visibility is needed either to transmit the sensor data being gathered, or to protect the team from hostile persons trying to approach the stationary UGVs.
9.	Anisi, David A., 1977-, et al. (author) Minimum time multi-UGV surveillance 2008 In: OPTIMIZATION AND COOPERATIVE CONTROL STRATEGIES. - Berlin : Springer Verlag. - 9783540880622 ; , s. 31-45 Conference paper (peer-reviewed)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.
10.	Anisi, David A., et al. (author) Safe receding horizon control of an aerial vehicle 2006 In: PROCEEDINGS OF THE 45TH IEEE CONFERENCE ON DECISION AND CONTROL, VOLS 1-14. - : IEEE. - 9781424401703 ; , s. 57-62 Conference paper (peer-reviewed)abstract This paper addresses the problem of designing a real time high performance controller and trajectory generator for air vehicles. The control objective is to use information about terrain and enemy threats to fly low and avoid radar exposure on the way to a given target. The proposed algorithm builds on the well known approach of Receding Horizon Control (RHC) combined with a terminal cost, calculated from a graph representation of the environment. Using a novel safety maneuver, and under an assumption on the maximal terrain inclination, we are able to prove safety as well as task completion. The safety maneuver is incorporated in the short term optimization, which is performed using Nonlinear Programming (NLP). Some key characteristics of the trajectory planner are highlighted through simulations.
11.	Anisi, David, et al. (author) On-line Trajectory planning for aerial vehicles : a safe approach with guaranteed task completion 2006 In: Collection of Technical Papers. - Reston, Virigina : American Institute of Aeronautics and Astronautics. - 9781563478192 - 1563478196 ; , s. 914-938 Conference paper (peer-reviewed)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 3 D 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.
12.	Anisi, David, et al. (author) Online Trajectory Planning for Aerial Vehicle : A Safe Approach with Guaranteed Task Completion Other publication (other academic/artistic)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.
13.	Bhat, Sriharsha, 1991-, et al. (author) A Cyber-Physical System for Hydrobatic AUVs : System Integration and Field Demonstration 2020 In: 2020 IEEE/OES Autonomous Underwater Vehicles Symposium, AUV 2020. - : Institute of Electrical and Electronics Engineers (IEEE). Conference paper (peer-reviewed)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.
14.	Bhat, Sriharsha, et al. (author) A Cyber-Physical System for Hydrobatic AUVs: System Integration and Field Demonstration 2020 Conference paper (peer-reviewed)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.
15.	Boström-Rost, Per, 1988- (author) On Informative Path Planning for Tracking and Surveillance 2019 Licentiate thesis (other academic/artistic)abstract This thesis studies a class of sensor management problems called informative path planning (IPP). Sensor management refers to the problem of optimizing control inputs for sensor systems in dynamic environments in order to achieve operational objectives. The problems are commonly formulated as stochastic optimal control problems, where to objective is to maximize the information gained from future measurements. In IPP, the control inputs affect the movement of the sensor platforms, and the goal is to compute trajectories from where the sensors can obtain measurements that maximize the estimation performance. The core challenge lies in making decisions based on the predicted utility of future measurements.In linear Gaussian settings, the estimation performance is independent of the actual measurements. This means that IPP becomes a deterministic optimal control problem, for which standard numerical optimization techniques can be applied. This is exploited in the first part of this thesis. A surveillance application is considered, where a mobile sensor is gathering information about features of interest while avoiding being tracked by an adversarial observer. The problem is formulated as an optimization problem that allows for a trade-off between informativeness and stealth. We formulate a theorem that makes it possible to reformulate a class of nonconvex optimization problems with matrix-valued variables as convex optimization problems. This theorem is then used to prove that the seemingly intractable IPP problem can be solved to global optimality using off-the-shelf optimization tools.The second part of this thesis considers tracking of a maneuvering target using a mobile sensor with limited field of view. The problem is formulated as an IPP problem, where the goal is to generate a sensor trajectory that maximizes the expected tracking performance, captured by a measure of the covariance matrix of the target state estimate. When the measurements are nonlinear functions of the target state, the tracking performance depends on the actual measurements, which depend on the target’s trajectory. Since these are unavailable in the planning stage, the problem becomes a stochastic optimal control problem. An approximation of the problem based on deterministic sampling of the distribution of the predicted target trajectory is proposed. It is demonstrated in a simulation study that the proposed method significantly increases the tracking performance compared to a conventional approach that neglects the uncertainty in the future target trajectory.
16.	Bull, Peter, et al. (author) Förstudie obemannade farkoster 2012 Reports (pop. science, debate, etc.)abstract Obemannade farkoster används allt oftare, och i allt fler roller, i dagens kon- flikter. Denna rapport ger en bred överblick över området militära obemannade farkoster, samt rekommendationer för inriktningen av framtida FoU-satsningar inom området.Överblicken över området har fokus på både system, förmågor och verksam- heter som är relevanta för Försvarsmakten. Genom att låta de insatsförmågor som definieras i FMUP (Försvarsmaktens utvecklingsplan) gå som en röd tråd genom rapporten, både när specifika system diskuteras och när möjliga scena- rier där obemannade farkoster kan vara till nytta beskrivs, har vi försökt hålla både bredd och relevans i dokumentet.Rekommendationerna vilar på en genomgång av de inriktningsdokument som producerats i Försvarsmakten, t.ex. Perspektivplanneringen och FMUP, besök vid de enheter som dagligen använder obemannade farkoster, UAV-enheten i Karlsborg och Swedec i Eksjö, samt den områdesöverblick som nämns ovan. Slutsatserna är att den effektivaste kompetensuppbyggnaden och kunskapsöver- föringen fås om man skapar breda tvärvetenskapliga projekt inom respektive systemkategori (UAV, UGV, etc) med nära kontakter till materielförsörjnings- processen och perspektivplaneringen. Dessa kan samla kompetensen inom FHS och FOI, övervaka forskningsfronten genom att bevaka tävlingar, konferenser samt delta i internationella samarbeten, samt överföra det samlade resultaten till Försvarsmakten genom demonstrationer av verkliga eller simulerade delsy- stem och interaktiva simuleringar av hela system. Just systemsimuleringar kan göras särskilt realistiska, eftersom interaktionen med de riktiga obemannade systemen till stor del sker igenom kontrollstationernas datorer. På så sätt ska- pas en känsla för både hot och möjligheter med de nya systemen, vilket gagnar både taktikutveckling och materielprocesser.
17.	Båberg, Fredrik, et al. (author) Adaptive object centered teleoperation control of a mobile manipulator 2016 In: 2016 IEEE International Conference on Robotics and Automation (ICRA). - : Institute of Electrical and Electronics Engineers (IEEE). - 9781467380263 ; , s. 455-461 Conference paper (peer-reviewed)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, supported by data from the wrist mounted RGB-D sensor. 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.
18.	Båberg, Fredrik, et al. (author) Extended version of Adaptive Object Centered Teleoperation Control of a Mobile Manipulator Other publication (other academic/artistic)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.
19.	Båberg, Fredrik, et al. (author) Formation Obstacle Avoidance using RRT and Constraint Based Programming 2017 In: 2017 IEEE International Symposium on Safety, Security and Rescue Robotics (SSRR). - : IEEE conference proceedings. - 9781538639221 Conference paper (peer-reviewed)abstract In this paper, we propose a new way of doing formation obstacle avoidance using a combination of Constraint Based Programming (CBP) and Rapidly Exploring Random Trees (RRTs). RRT is used to select waypoint nodes, and CBP is used to move the formation between those nodes, reactively rotating and translating the formation to pass the obstacles on the way. Thus, the CBP includes constraints for both formation keeping and obstacle avoidance, while striving to move the formation towards the next waypoint. The proposed approach is compared to a pure RRT approach where the motion between the RRT waypoints is done following linear interpolation trajectories, which are less computationally expensive than the CBP ones. The results of a number of challenging simulations show that the proposed approach is more efficient for scenarios with high obstacle densities.
20.	Båberg, Fredrik, et al. (author) Free Look UGV Teleoperation Control Tested in Game Environment : Enhanced Performance and Reduced Workload 2016 In: International Symposium on Safety,Security and Rescue Robotics. Conference paper (peer-reviewed)abstract Concurrent telecontrol of the chassis and camera ofan Unmanned Ground Vehicle (UGV) is a demanding task forUrban Search and Rescue (USAR) teams. The standard way ofcontrolling UGVs is called Tank Control (TC), but there is reasonto believe that Free Look Control (FLC), a control mode used ingames, could reduce this load substantially by decoupling, andproviding separate controls for, camera translation and rotation.The general hypothesis is that FLC (1) reduces robot operators’workload and (2) enhances their performance for dynamic andtime-critical USAR scenarios. A game-based environment wasset-up to systematically compare FLC with TC in two typicalsearch and rescue tasks: navigation and exploration. The resultsshow that FLC improves mission performance in both exploration(search) and path following (navigation) scenarios. In the former,more objects were found, and in the latter shorter navigationtimes were achieved. FLC also caused lower workload and stresslevels in both scenarios, without inducing a significant differencein the number of collisions. Finally, FLC was preferred by 75% of the subjects for exploration, and 56% for path following.
21.	Båberg, Fredrik (author) Improving Manipulation and Control of Search and Rescue UGVs Operating Across Autonomy Levels 2022 Doctoral thesis (other academic/artistic)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.
22.	Caccamo, Sergio, 1987- (author) Enhancing geometric maps through environmental interactions 2018 Doctoral thesis (other academic/artistic)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.
23.	Caccamo, Sergio, et al. (author) Extending a UGV Teleoperation FLC Interface with Wireless Network Connectivity Information 2015 In: 2015 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS). - : IEEE. - 9781479999941 ; , s. 4305-4312 Conference paper (peer-reviewed)abstract Teleoperated Unmanned Ground Vehicles (UGVs) are expected to play an important role in future search and rescue operations. In such tasks, two factors are crucial for a successful mission completion: operator situational awareness and robust network connectivity between operator and UGV. In this paper, we address both these factors by extending a new Free Look Control (FLC) operator interface with a graphical representation of the Radio Signal Strength (RSS) gradient at the UGV location. We also provide a new way of estimating this gradient using multiple receivers with directional antennas. The proposed approach allows the operator to stay focused on the video stream providing the crucial situational awareness, while controlling the UGV to complete the mission without moving into areas with dangerously low wireless connectivity. The approach is implemented on a KUKA youBot using commercial-off-the-shelf components. We provide experimental results showing how the proposed RSS gradient estimation method performs better than a difference approximation using omnidirectional antennas and verify that it is indeed useful for predicting the RSS development along a UGV trajectory. We also evaluate the proposed combined approach in terms of accuracy, precision, sensitivity and specificity.
24.	Caccamo, Sergio, et al. (author) RCAMP : A Resilient Communication-Aware Motion Planner for Mobile Robots with Autonomous Repair of Wireless Connectivity 2017 In: 2017 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS). - : IEEE. - 9781538626825 ; , s. 2010-2017 Conference paper (peer-reviewed)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.
25.	Christalin, B., et al. (author) Synthesis of reactive control protocols for switch electrical power systems for commercial application with safety specifications 2017 In: 2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016. - : IEEE. - 9781509042401 Conference paper (peer-reviewed)abstract This paper presents a method for the reactive synthesis of fault-tolerant optimal control protocols for a finite deterministic discrete event system subject to safety specifications. A Deterministic Finite State Machine (DFSM) and Behavior Tree (BT) were used to model the system. The synthesis procedure involves formulating the policy problem as a shortest path dynamic programming problem. The procedure evaluates all possible states when applied to the DFSM, or over all possible actions when applied to the BT. The resulting strategy minimizes the number of actions performed to meet operational objectives without violating safety conditions. The effectiveness of the procedure on DFSMs and BTs is demonstrated through three examples of switched electrical power systems for commercial application and analyzed using run-time complexity analysis. The results demonstrated that for large order system BTs provided a tractable model to synthesize an optimal control policy.
26.	Colledanchise, Michele (author) Behavior Trees in Robotics 2017 Doctoral thesis (other academic/artistic)abstract Behavior Trees (BTs) are a Control Architecture (CA) that was invented in the video game industry, for controlling non-player characters. In this thesis we investigate the possibilities of using BTs for controlling autonomous robots, from a theoretical as well as practical standpoint. The next generation of robots will need to work, not only in the structured assembly lines of factories, but also in the unpredictable and dynamic environments of homes, shops, and other places where the space is shared with humans, and with different and possibly conflicting objectives. The nature of these environments makes it impossible to first compute the long sequence of actions needed to complete a task, and then blindly execute these actions. One way of addressing this problem is to perform a complete re-planning once a deviation is detected. Another way is to include feedback in the plan, and invoke additional incremental planning only when outside the scope of the feedback built into the plan. However, the feasibility of the latter option depends on the choice of CA, which thereby impacts the way the robot deals with unpredictable environments. In this thesis we address the problem of analyzing BTs as a novel CA for robots. The philosophy of BTs is to create control policies that are both modular and reactive. Modular in the sense that control policies can be separated and recombined, and reactive in the sense that they efficiently respond to events that were not predicted, either caused by external agents, or by unexpected outcomes of robot's own actions. Firstly, we propose a new functional formulation of BTs that allows us to mathematically analyze key system properties using standard tools from robot control theory. In particular we analyze whenever a BT is safe, in terms of avoiding particular parts of the state space; and robust, in terms of having a large domain of operation. This formulation also allows us to compare BTs with other commonly used CAs such as Finite State Machines (FSMs); the Subsumption Architecture; Sequential Behavior Compositions; Decision Trees; AND-OR Trees; and Teleo-Reactive Programs. Then we propose a framework to systematically analyze the efficiency and reliability of a given BT, in terms of expected time to completion and success probability. By including these performance measures in a user defined objective function, we can optimize the order of different fallback options in a given BT for minimizing such function. Finally we show the advantages of using BTs within an Automated Planning framework. In particular we show how to synthesize a policy that is reactive, modular, safe, and fault tolerant with two different approaches: model-based (using planning), and model-free (using learning).
27.	Colledanchise, Michele, et al. (author) How Behavior Trees Generalize the Teleo-Reactive Paradigm and And-Or-Trees 2016 Conference paper (peer-reviewed)abstract Behavior Trees (BTs) is a way of organizing the switching structure of a control system, that was originally developed in the computer gaming industry but is now also being used in robotics. The Teleo-Reactive programs (TRs) is a highly cited reactive hierarchical robot control approach suggested by Nilsson and And-Or-Trees are trees used for heuristic problems solving. In this paper, we show that BTs generalize TRs as well as And-Or-Trees, even though the two concepts are quite different. And-Or-Trees are trees of conditions, and we show that they transform into a feedback execution plan when written as a BT. TRs are hierarchical control structures, and we show how every TR can be written as a BT. Furthermore, we show that so-called Universal TRs, guaranteeing that the goal will be reached, are a special case of so-called Finite Time Successful BTs. This implies that many designs and theoretical results developed for TRs can be applied to BTs.
28.	Colledanchise, Michele, et al. (author) How Behavior Trees Modularize Hybrid Control Systems and Generalize Sequential Behavior Compositions, the Subsumption Architecture, and Decision Trees 2017 In: IEEE Transactions on robotics. - : IEEE. - 1552-3098 .- 1941-0468. ; 33:2, s. 372-389 Journal article (peer-reviewed)
29.	Colledanchise, Michele, et al. (author) How Behavior Trees Modularize Robustness and Safety in Hybrid Systems 2014 In: 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, (IROS 2014). - : IEEE. - 9781479969340 ; , s. 1482-1488 Conference paper (peer-reviewed)abstract Behavior Trees (BTs) have become a popular framework for designing controllers of in-game opponents in the computer gaming industry. In this paper, we formalize and analyze the reasons behind the success of the BTs using standard tools of robot control theory, focusing on how properties such as robustness and safety are addressed in a modular way. In particular, we show how these key properties can be traced back to the ideas of subsumption and sequential compositions of robot behaviors. Thus BTs can be seen as a recent addition to a long research effort towards increasing modularity, robustness and safety of robot control software. To illustrate the use of BTs, we provide a set of solutions to example problems.
30.	Colledanchise, Michele, et al. (author) Learning of Behavior Trees for Autonomous Agents. Journal article (peer-reviewed)
31.	Colledanchise, Michele, et al. (author) Obstacle avoidance in formation using navigation-like functions and constraint based programming 2013 In: Proceedings of the International Conference on Intelligent Robots and Systems (IROS), 2013 IEEE/RSJ. - : IEEE conference proceedings. - 9781467363587 ; , s. 5234-5239 Conference paper (peer-reviewed)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.
32.	Colledanchise, Michele, 1987-, et al. (author) Robot navigation under uncertainties using event based sampling 2014 In: Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on. - : IEEE conference proceedings. ; , s. 1438-1445 Conference paper (peer-reviewed)abstract In many robot applications, sensor feedback is needed to reduce uncertainties in environment models. However, sensor data acquisition also induces costs in terms of the time elapsed to make the observations and the computations needed to find new estimates. In this paper, we show how to use event based sampling to reduce the number of measurements done, thereby saving time, computational resources and power, without jeopardizing critical system properties such as safety and goal convergence. This is done by combining recent advances in nonlinear estimation with event based control using artificial potential fields. The results are particularly useful for real time systems such as high speed vehicles or teleoperated robots, where the cost of taking measurements is even higher, in terms of stops or transmission times. We conclude the paper with a set of simulations to illustrate the effectiveness of the approach and compare it with a baseline approach using periodic measurements.
33.	Colledanchise, Michele, et al. (author) Stochastic Behavior Trees for Estimating and Optimizing the Performance of Reactive Plan Executions Journal article (peer-reviewed)
34.	Colledanchise, Michele, et al. (author) Synthesis of Correct-by-Construction Behavior Trees 2017 In: 2017 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS). - : IEEE. - 9781538626825 ; , s. 6039-6046 Conference paper (peer-reviewed)abstract In this paper we study the problem of synthesizing correct-by-construction Behavior Trees (BTs) controlling agents in adversarial environments. The proposed approach combines the modularity and reactivity of BTs with the formal guarantees of Linear Temporal Logic (LTL) methods. Given a set of admissible environment specifications, an agent model in form of a Finite Transition System and the desired task in form of an LTL formula, we synthesize a BT in polynomial time, that is guaranteed to correctly execute the desired task. To illustrate the approach, we present three examples of increasing complexity.
35.	Colledanchise, Michele, et al. (author) The advantages of using behavior trees in multi-robot systems 2016 In: 47th International Symposium on Robotics, ISR 2016. - : VDE Verlag GmbH. - 9783800742318 ; , s. 23-30 Conference paper (peer-reviewed)abstract Multi-robot teams offer possibilities of improved performance and fault tolerance, compared to single robot solutions. In this paper, we show how to realize those possibilities when starting from a single robot system controlled by a Behavior Tree (BT). By extending the single robot BT to a multi-robot BT, we are able to combine the fault tolerant properties of the BT, in terms of built-in fallbacks, with the fault tolerance inherent in multi-robot approaches, in terms of a faulty robot being replaced by another one. Furthermore, we improve performance by identifying and taking advantage of the opportunities of parallel task execution, that are present in the single robot BT. Analyzing the proposed approach, we present results regarding how mission performance is affected by minor faults (a robot losing one capability) as well as major faults (a robot losing all its capabilities).
36.	Colledanchise, Michele, et al. (author) Towards Blended Planning and Acting using Behavior Trees. A Reactive, Safe and Fault Tolerant Approach. Journal article (peer-reviewed)
37.	Colledanchise, Michele, et al. (author) Towards Blended Reactive Planning and Acting using Behavior Trees 2019 In: 2019 International Conference on Robotics And Automation (ICRA). - : IEEE Robotics and Automation Society. - 9781538660263 ; , s. 8839-8845 Conference paper (peer-reviewed)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.
38.	Colledancise, Michele, et al. (author) Learning of Behavior Trees for Autonomous Agents 2018 In: IEEE Transactions on Games. - : IEEE Press. - 2475-1502. Journal article (peer-reviewed)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.
39.	Egerstedt, M, et al. (author) Toward Optimal Control of Switched Linear Systems 2000 Conference paper (peer-reviewed)abstract We investigate the problem of driving the state of a switched linear control system between boundary states. We propose tight lower bounds for the minimum energy control problem. Furthermore, we show that the change of the system dynamics across the switching surface gives rise to phenomena that can be treated as a decidability problem of hybrid systems. Applying earlier results on controller synthesis for hybrid systems with linear continuous dynamics, we provide an algorithm for computing the minimum number of switchings of a trajectory from one state to another, and show that this algorithm is computable for a fairly wide class of linear switched systems
40.	Erlandsson, Tina, 1983- (author) A combat survivability model for evaluating air mission routes in future decision support systems 2014 Doctoral thesis (other academic/artistic)
41.	Gattami, Ather, et al. (author) Stabilization of Vehicle Formations-A Case Study 2005 In: Book of Abstracts of Third Swedish Workshop on Autonomous Robotics. - 1650-1942. Conference paper (other academic/artistic)abstract This work treats a specific multi-vehicle control case, namely six vehicles on the Multi-Vehicle Wireless Testbed (MTWT), wich is an arena at Caltech, California, built for doing experiments on small vehicles. A model is set up and a controller is found through simulations that stabilizes the system. Stability is proven through a Nyquist-like criterion.
42.	Iovino, Matteo, et al. (author) A survey of Behavior Trees in robotics and AI 2022 In: Robotics and Autonomous Systems. - : Elsevier BV. - 0921-8890 .- 1872-793X. ; 154 Journal article (peer-reviewed)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.
43.	Karayiannidis, Yiannis, 1980-, et al. (author) Adaptive force/velocity control for opening unknown doors 2012 In: Robot Control, Volume 10, Part 1. - 9783902823113 ; , s. 753-758 Conference paper (peer-reviewed)abstract The problem of door opening is fundamental for robots operating in domesticenvironments. Since these environments are generally unstructured, a robot must deal withseveral types of uncertainties associated with the dynamics and kinematics of a door to achievesuccessful opening. The present paper proposes a dynamic force/velocity controller which usesadaptive estimation of the radial direction based on adaptive estimates of the door hinge’sposition. The control action is decomposed into estimated radial and tangential directions,which are proved to converge to the corresponding actual values. The force controller usesreactive compensation of the tangential forces and regulates the radial force to a desired smallvalue, while the velocity controller ensures that the robot’s end-effector moves with a desiredtangential velocity. The performance of the control scheme is demonstrated in simulation witha 2 DoF planar manipulator opening a door.
44.	Karayiannidis, Yiannis, et al. (author) An Adaptive Control Approach for Opening Doors and Drawers Under Uncertainties 2016 In: IEEE Transactions on robotics. - : IEEE. - 1552-3098 .- 1941-0468. ; 32:1, s. 161-175 Journal article (peer-reviewed)abstract We study the problem of robot interaction with mechanisms that afford one degree of freedom motion, e.g., doors and drawers. We propose a methodology for simultaneous compliant interaction and estimation of constraints imposed by the joint. Our method requires no prior knowledge of the mechanisms' kinematics, including the type of joint, prismatic or revolute. The method consists of a velocity controller that relies on force/torque measurements and estimation of the motion direction, the distance, and the orientation of the rotational axis. It is suitable for velocity controlled manipulators with force/torque sensor capabilities at the end-effector. Forces and torques are regulated within given constraints, while the velocity controller ensures that the end-effector of the robot moves with a task-related desired velocity. We give proof that the estimates converge to the true values under valid assumptions on the grasp, and error bounds for setups with inaccuracies in control, measurements, or modeling. The method is evaluated in different scenarios involving opening a representative set of door and drawer mechanisms found in household environments.
45.	Karayiannidis, Yiannis, 1980-, et al. (author) Design of force-driven online motion plans for door opening under uncertainties 2012 In: Workshop on Real-time Motion Planning: Online, Reactive, and in Real-time. Conference paper (peer-reviewed)abstract The problem of door opening is fundamental for household robotic applications. Domestic environments are generally less structured than industrial environments and thus several types of uncertainties associated with the dynamics and kinematics of a door must be dealt with to achieve successful opening. This paper proposes a method that can open doors without prior knowledge of the door kinematics. The proposed method can be implemented on a velocity-controlled manipulator with force sensing capabilities at the end-effector. The velocity reference is designed by using feedback of force measurements while constraint and motion directions are updated online based on adaptive estimates of the position of the door hinge. The online estimator is appropriately designed in order to identify the unknown directions. The proposed scheme has theoretically guaranteed performance which is further demonstrated in experiments on a real robot. Experimental results additionally show the robustness of the proposed method under disturbances introduced by the motion of the mobile platform.
46.	Karayiannidis, Yiannis, 1980-, et al. (author) Interactive perception and manipulation of unknown constrained mechanisms using adaptive control 2013 In: ICRA 2013 Mobile Manipulation Workshop on Interactive Perception. Conference paper (peer-reviewed)
47.	Karayiannidis, Yiannis, 1980-, et al. (author) Model-free robot manipulation of doors and drawers by means of fixed-grasps 2013 In: 2013 IEEE International Conference on Robotics and Automation (ICRA). - New York : IEEE. - 9781467356411 ; , s. 4485-4492 Conference paper (peer-reviewed)abstract This paper addresses the problem of robot interaction with objects attached to the environment through joints such as doors or drawers. We propose a methodology that requires no prior knowledge of the objects’ kinematics, including the type of joint - either prismatic or revolute. The method consists of a velocity controller which relies onforce/torque measurements and estimation of the motion direction,rotational axis and the distance from the center of rotation.The method is suitable for any velocity controlled manipulatorwith a force/torque sensor at the end-effector. The force/torquecontrol regulates the applied forces and torques within givenconstraints, while the velocity controller ensures that the endeffectormoves with a task-related desired tangential velocity. The paper also provides a proof that the estimates converge tothe actual values. The method is evaluated in different scenarios typically met in a household environment.
48.	Karayiannidis, Yiannis, 1980-, et al. (author) "Open Sesame!" Adaptive Force/Velocity Control for Opening Unknown Doors 2012 In: Intelligent Robots and Systems (IROS), 2012 IEEE/RSJ International Conference on. - : IEEE. - 9781467317375 ; , s. 4040-4047 Conference paper (peer-reviewed)abstract The problem of door opening is fundamental for robots operating in domestic environments. Since these environments are generally less structured than industrial environments, several types of uncertainties associated with the dynamics and kinematics of a door must be dealt with to achieve successful opening. This paper proposes a method that can open doors without prior knowledge of the door kinematics. The proposed method can be implemented on a velocity-controlled manipulator with force sensing capabilities at the end-effector. The method consists of a velocity controller which uses force measurements and estimates of the radial direction based on adaptive estimates of the position of the door hinge. The control action is decomposed into an estimated radial and tangential direction following the concept of hybrid force/motion control. A force controller acting within the velocity controller regulates the radial force to a desired small value while the velocity controller ensures that the end effector of the robot moves with a desired tangential velocity leading to task completion. This paper also provides a proof that the adaptive estimates of the radial direction converge to the actual radial vector. The performance of the control scheme is demonstrated in both simulation and on a real robot.
49.	Kartasev, Mart, et al. (author) Improving the Performance of Backward Chained Behavior Trees that use Reinforcement Learning 2023 In: 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2023. - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 1572-1579 Conference paper (peer-reviewed)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.
50.	Kartasev, Mart, et al. (author) Improving the Performance of Learned Controllers in Behavior Trees Using Value Function Estimates at Switching Boundaries 2024 In: IEEE Robotics and Automation Letters. - : Institute of Electrical and Electronics Engineers (IEEE). - 2377-3766. ; 9:5, s. 4647-4654 Journal article (peer-reviewed)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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