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Titlebook: Distributed Autonomous Robotic Systems; 16th International S Julien Bourgeois,Jamie Paik,Abdallah Makhoul Conference proceedings 2024 The E

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發(fā)表于 2025-3-21 19:30:46 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱(chēng)Distributed Autonomous Robotic Systems
副標(biāo)題16th International S
編輯Julien Bourgeois,Jamie Paik,Abdallah Makhoul
視頻videohttp://file.papertrans.cn/282/281746/281746.mp4
概述Presents state of the art in autonomous systems composed of multiple robots, robotic modules, or robotic agents.Is scientific outcome of the 16th International Symposium on Distributed Autonomous Robo
叢書(shū)名稱(chēng)Springer Proceedings in Advanced Robotics
圖書(shū)封面Titlebook: Distributed Autonomous Robotic Systems; 16th International S Julien Bourgeois,Jamie Paik,Abdallah Makhoul Conference proceedings 2024 The E
描述.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..
出版日期Conference proceedings 2024
關(guān)鍵詞DARS 2022; DARS; Social Insect; Evolution Cooperation; Ethology; Social Physiology; Adaptation; Self-organi
版次1
doihttps://doi.org/10.1007/978-3-031-51497-5
isbn_softcover978-3-031-53703-5
isbn_ebook978-3-031-51497-5Series ISSN 2511-1256 Series E-ISSN 2511-1264
issn_series 2511-1256
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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Capital Formation and Its Sourcests to re-direct their communication resources to different neighbors according to the current propagation process to fulfill global broadcast requirements. Based on this method, we provide an approach to compute the expected time to broadcast the message to all nodes. Numerical examples are provided to illustrate the results.
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Crime, Unemployment and Deprivationenergy metrics over the collective, and identify several behaviors that are robust to changes in the sensor model and other parameters. Finally, we provide a demonstration of how this approach can be used for control of a swarm using a single controllable agent and global mode switching.
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Social Exploration in Robot Swarms,ny given environment. We demonstrate the ability of the swarm to explore complex environments with minimal information and highlight increased performance in relation to other swarm behaviours over 250 randomly generated environments.
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發(fā)表于 2025-3-22 20:14:16 | 只看該作者
,A Decentralized Cooperative Approach to?Gentle Human Transportation with?Mobile Robots Based on?Tac same value in a dynamical simulation and actual experiments. Additionally, we found that multijoint objects also can be transported with the proposed method, whereas the stable support of the object by each robot is reserved for future works.
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發(fā)表于 2025-3-23 00:09:12 | 只看該作者
Search Space Illumination of Robot Swarm Parameters for Trustworthy Interaction, swarm logistics case study where an operator requires two swarm behaviour modes with differing characteristic needs. In this example we illustrate how an operator might express preference, receive recommendations, and select their final swarm characteristics.
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,Receding Horizon Control on?the?Broadcast of?Information in?Stochastic Networks,ts to re-direct their communication resources to different neighbors according to the current propagation process to fulfill global broadcast requirements. Based on this method, we provide an approach to compute the expected time to broadcast the message to all nodes. Numerical examples are provided to illustrate the results.
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發(fā)表于 2025-3-23 09:20:45 | 只看該作者
,Characterization of?the?Design Space of?Collective Braitenberg Vehicles,energy metrics over the collective, and identify several behaviors that are robust to changes in the sensor model and other parameters. Finally, we provide a demonstration of how this approach can be used for control of a swarm using a single controllable agent and global mode switching.
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