An improved PSO-based approach with dynamic parameter tuning for cooperative multi-robot target searching in complex unknown environments

DOI10.1080/00207179.2013.794920zbMath1312.93004OpenAlexW2101040790MaRDI QIDQ5252950

Simon X. Yang, Yifan Cai

Publication date: 3 June 2015

Published in: International Journal of Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207179.2013.794920

zbMATH Keywords

particle swarm optimization (PSO)target searchingartificial potential fieldcomplex environmentmulti-robot cooperation

Mathematics Subject Classification ID

Discrete-time control/observation systems (93C55) Automated systems (robots, etc.) in control theory (93C85) Decentralized systems (93A14)

Related Items (2)

A comprehensive survey on particle swarm optimization algorithm and its applications ⋮ Behavior-based formation control of swarm robots

Cites Work

• Cross-coupled iterative learning control of systems with dissimilar dynamics: design and implementation
• A virtual structure approach to formation control of unicycle mobile robots using mutual coupling
• Fault-tolerant cooperative tasking for multi-agent systems
• Asynchronous consensus of continuous-time multi-agent systems with intermittent measurements
• An optimal cooperation in a team of agents subject to partial information

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