Novel potential-function-based control scheme for non-holonomic multi-agent systems to prevent the local minimum problem

Abstract

In this paper, we consider a control problem of a non-holonomic multi-agent system. We assume that agents and obstacles are in a circular shaped work area. We propose a novel potential-function-based control scheme that drives agents from the initial to the goal configuration while avoiding collision with other agents, obstacles, and the boundary of the work area. The control scheme enables agents to avoid being trapped at local minima by forcing them to exit from the regions that may contain local minima. A numerical simulation is presented to demonstrate the validity of the proposed control scheme.

Keywords:

• multi-agent systems
• non-holonomic systems
• potential function
• local minima
• obstacle avoidance

Acknowledgements

We would like to thank professor David Hull for his assistance for the optimisation-based controller in the simulation section.

Additional information

Notes on contributors

Makiko Okamoto

Makiko Okamoto received her BS and MS degrees in Aerospace Engineering from The University of Texas at Austin. She is currently working towards the PhD degree in Aerospace Engineering at The University of Texas at Austin. Her primary research interest lies in the field of guidance and control. She is currently conducting research in the area of cooperative control for multi-vehicle systems.

Maruthi R. Akella

Maruthi R. Akella holds the rank of Associate Professor with tenure with the Department of Aerospace Engineering and Engineering Mechanics at The University of Texas at Austin. He received his PhD in Aerospace Engineering from Texas A&M University. Prior to joining the UT Austin faculty, he was a post-doctoral fellow with the Yale University Center for Systems Science. Dr. Akella specialises in the dynamics and control of complex systems. His research spans the broad areas of spacecraft attitude dynamics, orbital mechanics, flight vehicle guidance, navigation, estimation theory, and nonlinear controls. His recent research addresses cooperative control and collaboration in swarm robots, robotic navigation without GPS, and uncertainty quantification in autonomous systems. He is also performing control theoretic investigations of autonomous space systems, as well as experimental validation of flow-control systems for high-speed and hypersonic vehicles. Dr. Akella currently serves as director of the Controls Lab for Distributed and Uncertain Systems. He is an Associate Fellow of the American Institute of Aeronautics and Astronautics (AIAA) and serves as Associate Editor for the AIAA Journal of Guidance, Control, and Dynamics (JGCD), the Journal of the Astronautical Sciences (JAS) and IEEE Transactions on Aerospace and Electronic Systems (T-AES).