Multi-Robot Systems and Cooperative Object Transport: Communications, Platforms, and Challenges
IEEE Open Journal of the Computer Society, 2023 Multi-robot systems gain considerable attention due to lower cost, better robustness, and higher scalability as compared with single-robot systems. Cooperative object transport, as a well-known use case of multi-robot systems, shows great potential in ...
Xing An +5 more
doaj +4 more sources
Optimization techniques for Multi-Robot Task Allocation problems: Review on the state-of-the-art
Robotics and Autonomous Systems, 2023 In the last years, Multi-Robot Systems (MRS) have experienced considerable recognition due to various possible real-world applications. Multi-Robot Task Allocation (MRTA) is among the most interesting MRS problems.
Hamza Chakraa, Dimitri Lefebvre
exaly +2 more sources
Multi-Agent Deep Reinforcement Learning for Multi-Robot Applications: A Survey
Sensors, 2023 Deep reinforcement learning has produced many success stories in recent years. Some example fields in which these successes have taken place include mathematics, games, health care, and robotics. In this paper, we are especially interested in multi-agent
AYAN Dutta, Dutta AYAN
exaly +2 more sources
Collaborative Multi-Robot Search and Rescue: Planning, Coordination, Perception, and Active Vision
IEEE Access, 2020 Search and rescue (SAR) operations can take significant advantage from supporting autonomous or teleoperated robots and multi-robot systems. These can aid in mapping and situational assessment, monitoring and surveillance, establishing communication ...
Jorge Pena Queralta +2 more
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A Multi-Robot Task Allocation Method Based on the Synergy of the K-Means++ Algorithm and the Particle Swarm Algorithm [PDF]
BiomimeticsAddressing challenges in the traditional K-means algorithm, such as the challenge of selecting initial clustering center points and the lack of a maximum limit on the number of clusters, and where the set of tasks in the clusters is not reasonably sorted
Youdong Yuan +3 more
doaj +2 more sources
Safe multi-agent reinforcement learning for multi-robot control
Artificial Intelligence, 2023 Shangding Gu, Yuanpei Chen, Yali Du
exaly +2 more sources
LAMP 2.0: A Robust Multi-Robot SLAM System for Operation in Challenging Large-Scale Underground Environments [PDF]
IEEE Robotics and Automation Letters, 2022 Search and rescue with a team of heterogeneous mobile robots in unknown and large-scale underground environments requires high-precision localization and mapping. This crucial requirement is faced with many challenges in complex and perceptually-degraded
Yun Chang +11 more
semanticscholar +1 more source
Research Progress of Multi-Robot Collaborative SLAM Technology [PDF]
Jisuanji gongcheng, 2022 Because of the limitations of single-robot Simultaneous Localization and Mapping(SLAM) technology in practical applications, multi-robot collaborative SLAM technology has received extensive attention from researchers with its strong flexibility and ...
LIU Xin, WANG Zhong, QIN Mingxing
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Research on Multi-robot Formation Control Based on Speed Compensation Algorithm [PDF]
Zhengzhou Daxue xuebao. Gongxue ban, 2022 In order to solve the problems of complex algorithm of traditional leader-follower method in formation control of multi-robot system and difficulty in completing circular formation of multi-robot system with common formation control law, the formation ...
ZHANG Fangfang +2 more
doaj +1 more source
Swarm-SLAM: Sparse Decentralized Collaborative Simultaneous Localization and Mapping Framework for Multi-Robot Systems [PDF]
IEEE Robotics and Automation Letters, 2023 Collaborative Simultaneous Localization And Mapping (C-SLAM) is a vital component for successful multi-robot operations in environments without an external positioning system, such as indoors, underground or underwater.
Pierre-Yves Lajoie, G. Beltrame
semanticscholar +1 more source