Design of a Robot Controller for Peloton Formation Using Fuzzy Logic

This paper presents a controller for the optimization of flocking and formation algorithm adapted from the flocking behavior of cycling team or pelotons. The controller developed is a fuzzy-logic controller for each of the robotic agent in order for them to perform a peloton formation. Results from the simulation shows that the developed fuzzy logic controller is slightly better than the mathematical models in maintaining a small and optimal position for the peloton formation which results to a more efficient and robust swarm system.

[1]  W. Marsden I and J , 2012 .

[2]  Richard M. Murray,et al.  Consensus problems in networks of agents with switching topology and time-delays , 2004, IEEE Transactions on Automatic Control.

[3]  Jinde Cao,et al.  Reverse Group Consensus of Multi-Agent Systems in the Cooperation-Competition Network , 2016, IEEE Transactions on Circuits and Systems I: Regular Papers.

[4]  Reza Olfati-Saber,et al.  Flocking for multi-agent dynamic systems: algorithms and theory , 2006, IEEE Transactions on Automatic Control.

[5]  Erick Martins Ratamero Modelling Peloton Dynamics in Competitive Cycling: A Quantitative Approach , 2013, icSPORTS 2013.

[6]  Gang Feng,et al.  Output Consensus of Heterogeneous Linear Multi-Agent Systems with Adaptive Event-Triggered Control , 2019, IEEE Transactions on Automatic Control.

[7]  Randal W. Beard,et al.  Consensus seeking in multiagent systems under dynamically changing interaction topologies , 2005, IEEE Transactions on Automatic Control.

[8]  Ron Goldman,et al.  An Asymmetric Distributed Method for Sorting a Robot Swarm , 2017, IEEE Robotics and Automation Letters.

[9]  Reza Olfati-Saber,et al.  Consensus and Cooperation in Networked Multi-Agent Systems , 2007, Proceedings of the IEEE.

[10]  Thomas Andrianne,et al.  Aerodynamic drag in cycling team time trials , 2018, Journal of Wind Engineering and Industrial Aerodynamics.