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[null,null,"Titolo",null,"Distributed Autonomous Robotic Systems : 16th International Symposium / / edited by Julien Bourgeois, Jamie Paik, Benoît Piranda, Justin Werfel, Sabine Hauert, Alyssa Pierson, Heiko Hamann, Tin Lun Lam, Fumitoshi Matsuno, Negar Mehr, Abdallah Makhoul"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024"]
[null,null,"ISBN",null,"3-031-51497-1"]
[null,null,"Edizione",null,"[1st ed. 2024.]"]
[null,null,"Descrizione fisica",null,"1 online resource (576 pages)"]
[null,null,"Collana",null,"Springer Proceedings in Advanced Robotics, , 2511-1264 ; ; 28"]
[null,null,"Disciplina",null,"629.892"]
[null,null,"Soggetti",null,"Automatic control"]
[{"$nulls":4},"Robotics"]
[{"$nulls":4},"Automation"]
[{"$nulls":4},"Computational intelligence"]
[{"$nulls":4},"Control, Robotics, Automation"]
[{"$nulls":4},"Computational Intelligence"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Intro -- Foreword -- Preface -- Contents -- How Can We Understand Multi-Robot Systems? a User Study to Compare Implicit and Explicit Communication Modalities -- 1 Introduction -- 2 Methods -- 2.1 Communication Modalities -- 2.2 Experimental Task -- 2.3 Experimental Setup -- 2.4 Participants -- 2.5 Data Collection and Analysis -- 3 Results -- 3.1 Correctness of Responses -- 3.2 Response Time -- 3.3 Subjective Reporting -- 4 Conclusion -- References -- The Benefits of Interaction Constraints in Distributed Autonomous Systems -- 1 Introduction -- 2 Collective Learning in Multi-agent Systems -- 3 A Three-Valued Model for Collective Learning -- 4 Simulation Environment -- 5 The Networks Underlying Agent Interactions -- 6 Multi-agent Simulation Experiments -- 6.1 Convergence Results for Physical Networks -- 7 Constraining the Interaction Network -- 7.1 Convergence Results for Constrained Interaction Networks -- 8 Conclusion and Future Work -- References -- Outlining the Design Space of eXplainable Swarm (xSwarm): Experts' Perspective -- 1 Introduction -- 2 Background and Related Work -- 3 Background and Related Work -- 3.1 Participants -- 3.2 Study Procedure and Design -- 3.3 Analysis -- 4 Results -- 4.1 Explanation Categories -- 4.2 "]
[{"$nulls":4},"Challenges Faced by Swarm Experts -- 5 Conclusion -- References -- VMAS: A Vectorized Multi-agent Simulator for Collective Robot Learning -- 1 Introduction -- 2 Related Work -- 3 The VMAS Platform -- 4 Multi-robot Scenarios -- 5 Comparison with MPE -- 6 Experiments and Benchmarks -- 7 Conclusion -- References -- FLAM: Fault Localization and Mapping -- 1 Introduction -- 2 Related Work and Background -- 2.1 Fault Detection -- 2.2 Risk Awareness -- 2.3 Distributed Storage -- 3 System Model -- 3.1 Risk Modelling -- 3.2 Feature Vectors -- 3.3 Fault Detection -- 3.4 Distributed Belief Map -- 3.5 Implementation -- 4 Simulations."]
[{"$nulls":4},"4.1 Experimental Setup -- 4.2 Results -- 5 Conclusion -- References -- Social Exploration in Robot Swarms -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Simulation and Local Swarm Behaviours -- 3.2 Generating Random Environments -- 3.3 Agents with ``Happiness'' -- 3.4 Social Exploration Algorithm -- 4 Results -- 4.1 Performance in Randomly Generated Environments -- 5 Conclusions and Future Work -- References -- Stochastic Nonlinear Ensemble Modeling and Control for Robot Team Environmental Monitoring -- 1 Introduction -- 2 Problem Formulation -- 2.1 Task Topology -- 2.2 Ensemble Model -- 3 Ensemble Model Control -- 3.1 Feedback Controller -- 3.2 Distributed Microscopic Algorithm -- 4 Simulation and Experimental Setup -- 5 Results -- 6 Discussion -- 7 Conclusion -- References -- A Decentralized Cooperative Approach to Gentle Human Transportation with Mobile Robots Based on Tactile Feedback -- 1 Introduction -- 2 Methodology -- 2.1 Flexible Tactile Sensors and Methods of Acquiring Force Information -- 2.2 Design of Control Law -- 3 Modeling and Simulation -- 3.1 Modeling -- 3.2 Simulation -- 4 Experiments -- 4.1 Experiment Setup -- 4.2 Experiment Result -- 5 Conclusion and Future Work -- References -- Sparse Sensing in Ergodic Optimization -- 1 Introduction -- 2 Prior Work -- 3 Sparse Sensing in Ergodic Optimization -- 3.1 Sparse Ergodic Optimization -- 3.2 Multi-agent Sparse Ergodic Optimization -- 4 Results and Discussion -- 4.1 Experimental Details -- 4.2 Single Agent Sensing Distribution -- 4.3 Multi-agent Sparse Ergodic Optimization -- 5 Conclusion -- References -- Distributed Multi-robot Tracking of Unknown Clustered Targets with Noisy Measurements -- 1 Introduction -- 2 Problem Formulation -- 2.1 Lloyd's Algorithm -- 3 Distributed Multi-target Tracking -- 3.1 Instantaneous State Estimation -- 3.2 Cumulative State Estimation."]
[{"$nulls":4},"3.3 Environment Approximation -- 3.4 Distributed Control -- 3.5 Algorithm Outline -- 4 Simulations -- 4.1 Qualitative Comparison -- 4.2 Quantitative Comparison -- 5 Conclusions -- References -- A Force-Mediated Controller for Cooperative Object Manipulation with Independent Autonomous Robots -- 1 Background -- 2 Related Work -- 3 Challenges and Assumptions -- 4 Control Methodology -- 4.1 Closed Loop Control Dynamics -- 4.2 Inertial Estimation and Error Compensation -- 4.3 Controller Stability -- 4.4 Task-Frame Switching -- 5 Experimental Validation -- 5.1 Implementation in Hardware -- 5.2 Implementation in Simulation -- 6 Results -- 6.1 Controller Performance Within Static Task Domain -- 6.2 Controller Performance with a Changing Task Domain -- 6.3 Multi-robot Performance with Changing Task Domain -- 7 Discussion -- References -- A Distributed Architecture for Onboard Tightly-Coupled Estimation and Predictive Control of Micro Aerial Vehicle Formations -- 1 Introduction -- 2 Problem Formulation -- 3 Methodology -- 3.1 Follower Estimation Scheme -- 3.2 Follower Controller Scheme -- 4 Experiments and Results -- 4.1 Formation Navigation -- 4.2 Formation Reconfiguration -- 4.3 Discussion -- 5 Conclusion -- References -- Search Space "]
[{"$nulls":4},"Illumination of Robot Swarm Parameters for Trustworthy Interaction -- 1 Introduction -- 2 Methodology -- 2.1 Scenario -- 2.2 Swarm Metrics -- 2.3 Map-Elites Illumination Algorithm Methodology -- 3 Results -- 3.1 Qualitative Analysis: Case Study -- 4 Conclusion and Future Work -- References -- Collective Gradient Following with Sensory Heterogeneous UAV Swarm -- 1 Introduction -- 2 Methodology -- 3 Experimental Setup -- 4 Results and Discussion -- 5 Conclusion -- References -- DAN: Decentralized Attention-Based Neural Network for the MinMax Multiple Traveling Salesman Problem -- 1 Introduction -- 2 Prior Works."]
[{"$nulls":4},"3 Problem Formulation -- 4 mTSP as an RL PROBLEM -- 5 DAN: Decentralized Attention-Based Network -- 6 Training -- 7 Experiments -- 7.1 Results -- 7.2 Discussion -- 8 Conclusion -- References -- Receding Horizon Control on the Broadcast of Information in Stochastic Networks -- 1 Introduction -- 2 Background and Problem Formulation -- 2.1 Graph Theory -- 2.2 Information Propagation Model -- 3 Methodology -- 3.1 Control Strategy -- 3.2 Expected Time to Broadcast Information -- 3.3 Robust Moment Closure -- 4 Numerical Evaluation and Discussions -- 5 Conclusions and Future Work -- References -- Adaptation Strategy for a Distributed Autonomous UAV Formation in Case of Aircraft Loss -- 1 Introduction -- 2 Adaptation Algorithm for a Decentralized UAV Formation -- 2.1 Distributed Autonomous System Model -- 2.2 Adaptation Strategy for a Distributed Autonomous System -- 3 Simulation Results and Discussion -- 4 Conclusions -- References -- DGORL: Distributed Graph Optimization Based Relative Localization of Multi-robot Systems -- 1 Introduction -- 2 Related Work -- 3 Problem Formulation and the Proposed DGORL Solution -- 3.1 Graph Formation -- 3.2 Expansion Through Transition -- 3.3 Optimization -- 4 Theoretical Analysis -- 5 Simulation Experiments and Results -- 6 Conclusion -- References -- Characterization of the Design Space of Collective Braitenberg Vehicles -- 1 Introduction -- 1.1 Related Work -- 2 Model and Simulation -- 2.1 Agent Model -- 2.2 World -- 2.3 Metrics -- 3 Emergent Behaviors -- 3.1 Behavior Characterization -- 3.2 General Observations -- 3.3 Love -- 3.4 Aggression -- 3.5 Fear -- 3.6 Curiosity -- 4 Conclusion and Outlook -- References -- Decision-Making Among Bounded Rational Agents -- 1 Introduction -- 2 Related Work -- 3 Problem Formulation -- 3.1 Multi-agent Markov Decision Process -- 3.2 Iterative Best Response for MMDPs -- 4 Methodology."]
[{"$nulls":4},"4.1 Bounded Rational Agents in Game-Theoretic Framework -- 4.2 Importance Sampling for Computing Bounded-Rational Strategies -- 5 Simulated Experiments -- 5.1 Simulation Setup -- 5.2 Results -- 6 Physical Experiments -- 7 Conclusion -- References -- Distributed Multi-robot Information Gathering Using Path-Based Sensors in Entropy-Weighted Voronoi Regions -- 1 Introduction -- 2 Problem Formulation -- 3 Distributed Information Gathering -- 3.1 Distributed Entropy Voronoi Partition and Planner (DEVPP) -- 3.2 Multi-agent Distributed Information-Theoretic Planner (MA-DITP) -- 3.3 Multi-agent Global Information-Theoretic Planner (MA-GITP) -- 4 Experiments and Results -- 5 Conclusion -- References -- Distributed Multiple Hypothesis Tracker for Mobile Sensor Networks -- 1 Introduction -- 2 Background -- 2.1 MHT Definition -- 2.2 Lloyd's Algorithm -- 3 Distributed Multiple Hypothesis Tracker -- 3.1 Assumptions -- 3.2 Track Exchange and Fusion -- 3.3 Importance Weighting Function -- 4 Results -- 4.1 Performance Metric -- 4.2 Stationary Targets -- 4.3 Dynamic Targets -- 4.4 Discussion -- 5 Conclusion -- References -- Distributed Multirobot Control for Non-cooperative Herding -- 1 Introduction -- 2 Prior Work -- 3 Problem "]
[{"$nulls":4},"Formulation -- 4 Controller Design -- 4.1 Approach 1: One Dog to One Sheep Allocation Based Approach -- 4.2 Approach 2: Iterative Distributed Reformulation of (12) -- 5 Results -- 5.1 Simulation Results -- 5.2 Robot Experiments -- 6 Conclusions -- 7  Appendix: Proof of Feasibility for Approach 1 -- References -- On Limited-Range Coverage Control for Large-Scale Teams of Aerial Drones: Deployment and Study -- 1 Introduction -- 2 Methods -- 2.1 Coverage Control Strategy -- 2.2 Simulation Protocol -- 2.3 Field Test Protocol -- 2.4 Metrics -- 3 Results and Discussion -- 3.1 Simulation Results -- 3.2 Results of Field Tests -- 4 Conclusions."]
[{"$nulls":4},"References."]
[null,null,null,"Sommario/riassunto","This book of the SPAR series contains 39 scientific articles presented in the Distributed Autonomous Robotic Systems conference organized in November 28–30, 2022, in Montbéliard, France. The contributions are covering a broad scope of topics within distributed robotics including mobile sensor networks, unmanned aerial vehicles, multi-agent systems, algorithms for multi-robot systems, modular robots, swarm robotics, and reinforcement learning or deep learning applied to multi-robot systems."]