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1.	Almeida, Diogo, 1991-, et al. (författare) Team KTH’s Picking Solution for the Amazon Picking Challenge 2016 2017 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.
2.	Andersson, Olov, 1979- (författare) Methods for Scalable and Safe Robot Learning 2017 Licentiatavhandling (övrigt vetenskapligt/konstnärligt)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.
3.	Boström-Rost, Per, 1988- (författare) On Informative Path Planning for Tracking and Surveillance 2019 Licentiatavhandling (övrigt vetenskapligt/konstnärligt)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.
4.	Båberg, Fredrik, et al. (författare) Adaptive object centered teleoperation control of a mobile manipulator 2016 Ingår i: 2016 IEEE International Conference on Robotics and Automation (ICRA). - : Institute of Electrical and Electronics Engineers (IEEE). - 9781467380263 ; , s. 455-461 Konferensbidrag (refereegranskat)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.
5.	Båberg, Fredrik, et al. (författare) Formation Obstacle Avoidance using RRT and Constraint Based Programming 2017 Ingår i: 2017 IEEE International Symposium on Safety, Security and Rescue Robotics (SSRR). - : IEEE conference proceedings. - 9781538639221 Konferensbidrag (refereegranskat)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.
6.	Båberg, Fredrik, et al. (författare) Free Look UGV Teleoperation Control Tested in Game Environment : Enhanced Performance and Reduced Workload 2016 Ingår i: International Symposium on Safety,Security and Rescue Robotics. Konferensbidrag (refereegranskat)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.
7.	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.
8.	Caccamo, Sergio, et al. (författare) Extending a UGV Teleoperation FLC Interface with Wireless Network Connectivity Information 2015 Ingår i: 2015 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS). - : IEEE. - 9781479999941 ; , s. 4305-4312 Konferensbidrag (refereegranskat)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.
9.	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.
10.	Christalin, B., et al. (författare) Synthesis of reactive control protocols for switch electrical power systems for commercial application with safety specifications 2017 Ingår i: 2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016. - : IEEE. - 9781509042401 Konferensbidrag (refereegranskat)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.
11.	Colledanchise, Michele (författare) Behavior Trees in Robotics 2017 Doktorsavhandling (övrigt vetenskapligt/konstnärligt)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).
12.	Colledanchise, Michele, et al. (författare) How Behavior Trees Generalize the Teleo-Reactive Paradigm and And-Or-Trees 2016 Konferensbidrag (refereegranskat)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.
13.	Colledanchise, Michele, et al. (författare) How Behavior Trees Modularize Hybrid Control Systems and Generalize Sequential Behavior Compositions, the Subsumption Architecture, and Decision Trees 2017 Ingår i: IEEE Transactions on robotics. - : IEEE. - 1552-3098 .- 1941-0468. ; 33:2, s. 372-389 Tidskriftsartikel (refereegranskat)
14.	Colledanchise, Michele, et al. (författare) Synthesis of Correct-by-Construction Behavior Trees 2017 Ingår i: 2017 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS). - : IEEE. - 9781538626825 ; , s. 6039-6046 Konferensbidrag (refereegranskat)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.
15.	Colledanchise, Michele, et al. (författare) The advantages of using behavior trees in multi-robot systems 2016 Ingår i: 47th International Symposium on Robotics, ISR 2016. - : VDE Verlag GmbH. - 9783800742318 ; , s. 23-30 Konferensbidrag (refereegranskat)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).
16.	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.
17.	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.
18.	Karayiannidis, Yiannis, et al. (författare) An Adaptive Control Approach for Opening Doors and Drawers Under Uncertainties 2016 Ingår i: IEEE Transactions on robotics. - : IEEE. - 1552-3098 .- 1941-0468. ; 32:1, s. 161-175 Tidskriftsartikel (refereegranskat)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.
19.	Kruijff-Korbayová, I, et al. (författare) 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.
20.	Lundberg, I., et al. (författare) Intrinsic camera and hand-eye calibration for a robot vision system using a point marker 2015 Ingår i: IEEE-RAS International Conference on Humanoid Robots. - : IEEE Computer Society. - 9781479971749 ; , s. 59-66 Konferensbidrag (refereegranskat)abstract Accurate robot camera calibration is a requirement for vision guided robots to perform precision assembly tasks. In this paper, we address the problem of doing intrinsic camera and hand-eye calibration on a robot vision system using a single point marker. This removes the need for using bulky special purpose calibration objects, and also facilitates on line accuracy checking and re-calibration when needed, without altering the robots production environment. The proposed solution provides a calibration routine that produces high quality results on par with the robot accuracy and completes a calibration in 3 minutes without need of manual intervention. We also present a method for automatic testing of camera calibration accuracy. Results from experimental verification on the dual arm concept robot FRIDA are presented.
21.	McGhan, C. L. R., et al. (författare) Towards architecture-wide analysis, verification, and validation for total system stability during goal-seeking space robotics operations 2016 Ingår i: AIAA Space and Astronautics Forum and Exposition, SPACE 2016. - Reston, Virginia : American Institute of Aeronautics and Astronautics. Konferensbidrag (refereegranskat)abstract In this paper we discuss the beginnings of an attempt to define and analyze the stability of an entire modular robotic system architecture - one which includes a three-tier (3T) layer breakdown of capabilities, with symbolic, deterministic planning at the highest level. We approach the problem from the standpoint of a control theory outlook, and try to formalize the issues that result from trying to quantitatively characterize the overall performance of a well-defined system without a need for exhaustive testing. We start by discussing the concept of bounded-input bounded-output stability, giving examples where the technique might not be sufficient to guarantee what we term “total system stability” due to complications associated with the levels of abstraction between the modules and components that are being chained together in the architecture. We then go on to discuss necessary conditions that may fall out of this naturally as a result. We further try to better-define the input and output constraints needed to guarantee total system stability, using an assumption-guarantee-like contractual framework that sits alongside the architecture; the requirements then may have influence across multiple modules, in order to keep consistency. We also discuss how the structure of the architectural modules may help or hinder the process of capability characterization and performance analysis of each module and a given architecture configuration as a whole. We then discuss two overlapping methods that, combined, should allow us to analyze the effectiveness of the architecture, and help towards verification and validation of both the components and the system as a whole. Demonstrative examples are given using a specific architectural implementation called the Resilient Spacecraft Executive. In future work, we hope to define both necessary and sufficient conditions for total system stability across such a system architecture for robotics use.
22.	Parasuraman, Ramviyas, et al. (författare) A New UGV Teleoperation Interface for Improved Awareness of Network Connectivity and Physical Surroundings 2017 Ingår i: Journal of Human-Robot Interaction. - : Journal of Human-Robot Interaction. - 2163-0364. ; 6:3, s. 48-70 Tidskriftsartikel (refereegranskat)abstract A reliable wireless connection between the operator and the teleoperated unmanned ground vehicle (UGV) is critical in many urban search and rescue (USAR) missions. Unfortunately, as was seen in, for example, the Fukushima nuclear disaster, the networks available in areas where USAR missions take place are often severely limited in range and coverage. Therefore, during mission execution, the operator needs to keep track of not only the physical parts of the mission, such as navigating through an area or searching for victims, but also the variations in network connectivity across the environment. In this paper, we propose and evaluate a new teleoperation user interface (UI) that includes a way of estimating the direction of arrival (DoA) of the radio signal strength (RSS) and integrating the DoA information in the interface. The evaluation shows that using the interface results in more objects found, and less aborted missions due to connectivity problems, as compared to a standard interface. The proposed interface is an extension to an existing interface centered on the video stream captured by the UGV. But instead of just showing the network signal strength in terms of percent and a set of bars, the additional information of DoA is added in terms of a color bar surrounding the video feed. With this information, the operator knows what movement directions are safe, even when moving in regions close to the connectivity threshold.
23.	Parasuraman, Ramviyas, et al. (författare) 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.
24.	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.
25.	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.
26.	Tardioli, Danilo, et al. (författare) 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.
27.	Wang, Yuquan, 1985-, et al. (författare) Cooperative control of a serial-to-parallel structure using a virtual kinematic chain in a mobile dual-arm manipulation application 2015 Ingår i: Intelligent Robots and Systems (IROS), 2015 IEEE/RSJ International Conference on. - Hamburg, Germany : IEEE Robotics and Automation Society. - 2153-0858 .- 2153-0866. ; , s. 2372-2379 Konferensbidrag (refereegranskat)abstract In the future mobile dual-arm robots are expected to perform many tasks. Kinematically, the configuration of two manipulators that branch from the same common mobile base results in a serial-to-parallel kinematic structure, which makes inverse kinematic computations non-trivial. The motion of the base has to be decided in a trade-off, taking the needs of both arms into account. We propose to use a Virtual Kinematic Chain (VKC) to specify the common motion of the parallel manipulators, instead of using the two manipulators kinematics directly. With this VKC, we formulate a constraint based programming solution for the robot to respond to external disturbances during task execution. The proposed approach is experimentally verified both in a noise-free illustrative simulation and a real human robot co-manipulation task.
28.	Wang, Yuquan, 1985- (författare) Reactive control and coordination of redundant robotic systems 2016 Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract Redundant robotic systems, in terms of manipulators with one or twoarms, mobile manipulators, and multi-agent systems, have received an in-creasing amount of attention in recent years. In this thesis we describe severalways to improve robotic system performance by exploiting the redundancy.As the robot workspace becomes increasingly dynamic, it is common towork with imperfect geometric models of the robots or its workspace. Inorder to control the robot in a robust way in the presence of geometric uncer-tainties, we propose to assess the stability of our controller with respect to acertain task by deriving bounds on the geometric uncertainties. Preliminaryexperimental results support the fact that stability is ensured if the proposedbounds on the geometric uncertainties are fulfilled.As a non-contact measurement, computer vision could provide rich infor-mation for robot control. We introduce a two step method that transformsthe position-based visual servoing problem into a quadratic optimization prob-lem with linear constraints. This method is optimal in terms of minimizinggeodesic distance and allows us to integrate constraints, e.g. visibility con-straints, in a natural way.In the case of a single robot with redundant degrees of freedom, we canspecify a family of complex robotic tasks using constraint based programming(CBP). CBP allows us to represent robotic tasks with a set of equality andinequality constraints. Using these constraints we can formulate quadraticprogramming problems that exploit the redundancy of the robot and itera-tively resolve the trade-off between the different constraints. For example, wecould improve the velocity or force transmission ratios along a task-dependent direction using the priorities between different constraints in real time.Using the reactiveness of CBP, we formulated and implemented a dual-armpan cleaning task. If we mount a dual-arm robot on a mobile base, we proposeto use a virtual kinematic chain to specify the coordination between the mobilebase and two arms. Using the modularity of the CBP, we can integrate themobility and dual-arm manipulation by adding coordination constraints intoan optimization problem where dual-arm manipulation constraints are alreadyspecified. We also found that the reactiveness and modularity of the CBPapproach is important in the context of teleoperation. Inspired by the 3Ddesign community, we proposed a teleoperation interface control mode thatis identical to the ones being used to locally navigate the virtual viewpoint ofmost Computer Aided Design (CAD) softwares.In the case of multiple robots, we combine ideas from multi-agent coopera-tive coverage control, with problem formulations from the resource allocationfield, to create a distributed convergent approach to the resource positioningproblem.
29.	Wang, Yuquan, 1985-, et al. (författare) Whole Body Control of a Dual-Arm Mobile Robot Using a Virtual Kinematic Chain 2016 Ingår i: International Journal of Humanoid Robotics. - : WORLD SCIENTIFIC PUBL CO PTE LTD. - 0219-8436. ; 13:1 Tidskriftsartikel (refereegranskat)abstract Dual-arm manipulators have more advanced manipulation abilities compared to single-arm manipulators and manipulators mounted on a mobile base have additional mobility and a larger workspace. Combining these advantages, mobile dual-arm robots are expected to perform a variety of tasks in the future. Kinematically, the configuration of two arms that branches from the mobile base results in a serial-to-parallel kinematic structure. In order to respond to external disturbances, this serial-to-parallel kinematic structure makes inverse kinematic computations non-trivial, as the motion of the base has to take the needs of both arms into account. Instead of using the dual-arm kinematics directly, we propose to use a virtual kinematic chain (VKC) to specify the common motion of the two arms. We formulate a constraint-based programming solution which consists of two parts. In the first part, we use an extended serial kinematic chain including the mobile base and the VKC to formulate constraints that realize the desired orientation and translation expressed in the world frame. In the second part, we use the resolved VKC motion to constrain the common motion of the two arms. In order to explore the redundancy of the two arms in an optimization framework, we also provide a VKC-oriented manipulability measure as well as its closed-form gradient. We verify the proposed approach with simulations and experiments that are performed on a PR2 robot, which has two 7 degrees of freedom (DoF) arms and a 3 DoF mobile base.
30.	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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