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2023 IEEE International symposium on robotic and Sensors Environments, ROSE 2023

作者： Abouheaf, Mohammed Gueaieb, Wail Mayyas, Mohammad Bowling Green State University Robotics Engineering Bowling GreenOH43403 United States Ottawa University School of Electrical Engineering and Computer Science OttawaONK1N 6N5 Canada

ISBN: (纸本)9798350308044

This paper introduces an innovative data-driven approach for replicating behaviors in interconnected and heterogeneous dynamic systems. The core concept involves real-time control of dynamic systems to closely mimic reference-model trajectories using model-free techniques. Within this coupled framework, one component possesses complete information about reference-trajectories, although not necessarily their dynamics. In contrast, follower systems, with limited connectivity to reference-model trajectories, exclusively replicate the behavior of the primary process, which retains insight into model-reference dynamics. The adopted strategies are causal, integrating higher-order error dynamics to ensure precise tracking of reference-trajectories. Furthermore, these strategies incorporate variations in reference-model dynamics via a pseudo partial derivative, akin to sensitivity derivatives in model-reference adaptive strategies. To optimize the dynamic behavior of the follower process, the solution employs a reinforcement learning mechanism through adaptive critics. This mechanism approximates the optimal strategy and the associated value function. The actor and critic weights of the adaptive critic structure are tuned using a projection technique to ensure convergence of the adapted strategy. The validation of this solution is demonstrated on a dynamic system with delays, simulating an underwater vehicle scenario. The developed methodology is rigorously compared with another high-order model-free adaptive control approach. The presented approach showcases its capability to effectively replicate behaviors, resulting in improved tracking accuracy. © 2023 IEEE.

关键词： Trajectories

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15th International symposium on Distributed Autonomous robotic systems, DARS 2021 and 4th International symposium on Swarm Behavior and Bio-Inspired robotics, SWARM 2021

15th International Symposium on Distributed Autonomous Robot...

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15th International symposium on Distributed Autonomous robotic systems, DARS 2021 and 4th International symposium on Swarm Behavior and Bio-Inspired robotics, SWARM 2021

ISBN: (纸本)9783030927899

The proceedings contain 33 papers. The special focus in this conference is on Distributed Autonomous robotic systems. The topics include: Distributed Cooperative Localization with Efficient Pairwise Range Measurements;Robust Localization for Multi-robot Formations: An Experimental Evaluation of an Extended GM-PHD Filter;opportunistic Multi-robot Environmental Sampling via Decentralized Markov Decision Processes;A PHD Filter Based Localization System for robotic Swarms;an Innate Motivation to Tidy Your Room: Online Onboard Evolution of Manipulation behaviors in a Robot Swarm;multi-agent Reinforcement learning and Individuality Analysis for Cooperative Transportation with Obstacle Removal;battery Variability Management for Swarms;spectral-Based Distributed Ergodic Coverage for Heterogeneous Multi-agent Search;multi-agent Deception in Attack-Defense Stochastic Game;leading a Swarm with Signals;tractable Planning for Coordinated Story Capture: Sequential Stochastic Decoupling;errors in Collective robotic Construction;optimal Multi-robot Perimeter Defense Using Flow Networks;classification-Aware Path Planning of Network of Robots;Monitoring and Mapping of Crop Fields with UAV Swarms Based on Information Gain;a Discrete Model of Collective Marching on Rings;map learning via adaptive Region-Based Sampling in Multi-robot systems;collective Transport via Sequential Caging;reactiveBuild: Environment-adaptive Self-Assembly of Amorphous Structures;processes for a Colony Solving the Best-of-N Problem Using a Bipartite Graph Representation;byzantine Fault Tolerant Consensus for Lifelong and Online Multi-robot Pickup and Delivery;decentralized Navigation in 3D Space of a robotic Swarm with Heterogeneous Abilities;using Reinforcement learning to Herd a robotic Swarm to a Target Distribution;preservation of Giant Component Size After Robot Failure for Robustness of Multi-robot Network;swarm Localization Through Cooperative Landmark Identification;decentralized Multi-robot Planning i

关键词： Motion planning

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Behavior Replication of Cascaded Dynamic systems Using Machine learning

Behavior Replication of Cascaded Dynamic Systems Using Machi...

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International Workshop on Robot Sensing (ROSE)

作者： Mohammed Abouheaf Wail Gueaieb Mohammad Mayyas Robotics Engineering Bowling Green State University Bowling Green OH 43403 USA School of Electrical Engineering and Computer Science Ottawa University Ottawa Ontario K1N 6N5 Canada

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Applying adaptive control in modeling human motion behaviors in reinforcement robotic learning from demonstrations

Applying adaptive control in modeling human motion behaviors...

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2016 AAAI Fall symposium

作者： Tan, Huan Zhao, Yang Kannan, Balajee GE Global Research 1 Research Circle NiskayunaNY12309 United States

ISBN: (纸本)9781577357759

In this paper, we propose to use an adaptive control method as the basis of a reinforcement learning algorithm for robotic imitation learning. In the learning stage, robots use adaptive control method-based reinforcement learning algorithm to learn the parameters of dynamical systems. In the generation stage, robots use the learned dynamic system parameters and the pre-defined controller to drive the configuration states of the robot to move along desired state trajectories. One simulation experiment and one practical experiment on a robot are carried out to validate the effectiveness of our algorithm. The experimental results validate that the learning of the system parameters converges very fast and the learning results can improve the system performance of generating similar motion trajectories. Copyright © 2016, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Robots

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Proceedings of the 2008 ecsis symposium on learning and adaptive behaviors for robotic systems, LAB-RS 2008

Proceedings of the 2008 ECSIS Symposium on Learning and Adap...

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2008 ecsis symposium on learning and adaptive behaviors for robotic systems, LAB-RS 2008

ISBN: (纸本)9780769532721

The proceedings contain 19 papers. The topics discussed include: mixture model segmentation for gait recognition;what is an appropriate theory of limitation for a robot learner?;drumming with a humanoid robot: results from human-robot interaction studies;movement times in inter- and intrapersonal human coordination;improving robotic system robustness via a generalised formal artificial neural system;scalable biologically inspired neural networks with spike time based learning;recurrent neural associative learning of forward and inverse kinematics for movement generation of the redundant PA-10 robot;evolvability of neuromodulated learning for robots;learning vision algorithms for real mobile robots with genetic programming;towards object classification using 3D sensor data;learning robot dynamics for computed torque control using local Gaussian processes regression;and surprise-based learning for developmental robotics.

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Analyzing Collective Behavior in Evolutionary Swarm robotic systems Based on an Ethological Approach

Analyzing Collective Behavior in Evolutionary Swarm Robotic ...

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4th IEEE International symposium on adaptive Dynamic Programming and Reinforcement learning (ADPRL)

作者： Yasuda, Toshiyuki Wada, Nanami Ohkura, Kazuhiro Matsumura, Yoshiyuki Hiroshima Univ Grad Sch Engn 1-4-1 Kagamiyama Higashihiroshima 7398527 Japan Shinshu Univ Fac Text Sci & Technol Ueda Nagano 3868567 Japan

ISBN: (纸本)9781467359252

Swarm robotic systems are a type of multi-robot systems which generally consist of many homogeneous autonomous robots without any type of global controllers. Swarm robotics aims at designing desired collective behaviors through many interactions with other robots or their environment. Since a robotic swarm is controlled by an emergent way such as a result of self-organization by using robot learning or artificial evolution, no method has been known to grasp the macroscopic collective behavior in a practical sense, according to the best of our knowledge. In this paper, we propose a novel method for analyzing the collective behavior by introducing the concept of behavioral sequence, which stems from ethology. Analysis about behavioral sequence reveals the transition of robot's action from the viewpoint of specialization and helps us to understand the role of subgroups in a robotic swarm. Applying this method, we observe collective behavior in a foraging task of autonomous mobile robots.

关键词： Swarm robotics Evolutionary robotics Behavior Analysis Task Allocation Clustering Ethology Behavioral Sequence

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Proceedings of the 2008 ecsis symposium on learning and adaptive behaviors for robotic systems, LAB-RS 2008: Preface

Proceedings of the 2008 ECSIS Symposium on Learning and Adap...

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Proceedings of the 2008 ecsis symposium on learning and adaptive behaviors for robotic systems, LAB-RS 2008 2008年 vii页

作者： Stoica, Adrian Tunstel, Eddie Huntsberger, Terry Arslan, Tughrul Vijayakumar, Sethu El-Rayis, Ahmed O. ECSIS/UoE/JPL Applied Physics Laboratory John Hopkins University United States NASA Jet Propulsion Laboratory United States University of Edinburgh United Kingdom

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ISBN: (纸本)9780769532721

No abstract available

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Analyzing collective behavior in evolutionary swarm robotic systems based on an ethological approach

Analyzing collective behavior in evolutionary swarm robotic ...

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IEEE symposium on adaptive Dynamic Programming and Reinforcement learning, (ADPRL)

作者： Toshiyuki Yasuda Nanami Wada Kazuhiro Ohkura Yoshiyuki Matsumura Graduate School of Engineering Hiroshima University Higashi-Hiroshima JAPAN Faculty of Textile Science and Technology Shinshu University Ueda Nagano JAPAN

关键词： Robot kinematics Robot sensing systems Mobile robots Vectors Resource management Dynamic programming

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Monitoring Strategies for adaptive Periodic Control in Behavior-based robotic systems

Monitoring Strategies for Adaptive Periodic Control in Behav...

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ecsis symposium on Advanced Technologies for Enhanced Quality of Life (AT-EQUAL 2009)

作者： Burattini, Ernesto Finzi, Alberto Rossi, Silvia Staffa, Mariacarla Univ Naples Federico II Dipartimento Sci Fisiche Naples Italy Univ Naples Federico II Dipartimento Informat & Sistemist Naples Italy

ISBN: (纸本)9780769537535

The main goal of our current research is the design of a behavior-based robotic architecture that has the capability of adapting its behaviors to the rate of change of both the environment and its internal states reducing the computational costs of input processing. Inspired by research on biological clocks, we introduced a simple schema theory model where releasing mechanisms are combined with adaptive internal clocks. In this paper, we describe the design and development of a complete robotic architecture implementing this model. In particular, we considered a mobile robot domain that simulates the navigation behavior of a Catagliphys ant enhanced with simple visual capabilities.

关键词： Mobile robots

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Improving robotic system robustness via a generalised formal artificial neural system

Improving robotic system robustness via a generalised formal...

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ecsis symposium on learning and adaptive behaviors for robotic systems

作者： Howells, Gareth Sirlantzis, Konstantinos Univ Kent Dept Elect Canterbury Kent England

ISBN: (纸本)9780769532721

A major concern for robotic guidance systems is that a temporary or permanent failure of a given sensor within the system will erroneously trigger a potential system failure state. This paper introduces a generalised artificial neural system which is capable of addressing such problems by means of the inclusion of a weight value able to incorporate a distinct failure value. This will serve to significantly improve the performance and reliability of the guidance system.

关键词： systems engineering

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