Formation control has attracted much attention due to its successful application in ocean monitoring and its potential military and civil values (e.g., homeland security, disaster search and rescue, planet exploration and epidemic disinfection). When performing complex tasks, multi-agent systems are ...
Formation control has attracted much attention due to its successful application in ocean monitoring and its potential military and civil values (e.g., homeland security, disaster search and rescue, planet exploration and epidemic disinfection). When performing complex tasks, multi-agent systems are inevitably subject to many complex time constraints (e.g., the limited reaching time, intermittent control and etc.) and spatial constraints (the boundedness of state, control and motion, obstacle avoidance and etc.), which leads to the poor performances of the current unconstrained, formation controllers in practical applications. More importantly, the complex environment not only causes the system to have unknown time-varying disturbances and time-space variable nonlinear dynamics, but also causes network delays and switching. All of the above complex spatiotemporal constraints bring many challenges to the formation control. It is noted that most unmanned aircrafts and underwater vehicles have complicated mechanical and electronic structures. At the same time, they are required to move in various complex environmental scenarios. Hence their dynamics are difficult to model. It is very important to discover intelligent algorithms for geometric formation tracking that doesn’t (weakly) rely on the system model.
The goal of this Research Topic is to provide a timely discussion for researchers on the hotspots and challenges of study on formation in theoretical models and applied systems. Therefore, we welcome authors to submit original research and review articles to this Research Topic. Potential topics to be covered include, but are not limited to:
• Formation tracking and coordinated path-following
• Rigid formation and formation flight
• formation enclosing and coordinated enclosing
• Adaptive formation systems
• Fuzzy adaptive formation systems
• Finite-time formation systems
• Multi-agent Reinforcement Learning
• Adaptive neural networks in complex formation systems
• Reinforcement Learning in complex formation systems
• Applications in collective robotics, UAVs, UUVs and so on
Formation, Reinforcement Learning, Adaptive formation, Adaptive neural networks
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