Collision Avoidance of Multiagent Systems on Riemannian Manifolds

2022 ◽  
Vol 60 (1) ◽  
pp. 168-188
Author(s):  
Jacob R. Goodman ◽  
Leonardo J. Colombo
2013 ◽  
Vol 2013 ◽  
pp. 1-18 ◽  
Author(s):  
Yeong-Hwa Chang ◽  
Chun-Lin Chen ◽  
Wei-Shou Chan ◽  
Hung-Wei Lin ◽  
Chia-Wen Chang

This paper aims to investigate the formation control of leader-follower multiagent systems, where the problem of collision avoidance is considered. Based on the graph-theoretic concepts and locally distributed information, a neural fuzzy formation controller is designed with the capability of online learning. The learning rules of controller parameters can be derived from the gradient descent method. To avoid collisions between neighboring agents, a fuzzy separation controller is proposed such that the local minimum problem can be solved. In order to highlight the advantages of this fuzzy logic based collision-free formation control, both of the static and dynamic leaders are discussed for performance comparisons. Simulation results indicate that the proposed fuzzy formation and separation control can provide better formation responses compared to conventional consensus formation and potential-based collision-avoidance algorithms.


Author(s):  
Mishal Assif ◽  
Ravi Banavar ◽  
Anthony Bloch ◽  
Margarida Camarinha ◽  
Leonardo Colombo

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