Projects:2019s2-23301 Robust Formation Control for Multi-Vehicle Systems

Formation control has been widely used in the control of robots, sicne it can improve the overall efficency of the system. In this project, we aim to design a robust formation control for multi-vehicle system, in which the system can deal with at least one network problem or physical failure.

Introduction

Formation control of multi-agent systems (MASs) has been widely used for cooperative tasks in such applications as terrain exploration, mobile networks and traffic control. However, the communication-induced problems and the high failure risk of increasingequipment has created a number of challenges for the security of MASs. The objective of this project is to design a robust formation control strategy for a multi-vehicle system against communication/physical failures (e.g., network attacks, link failures, packet dropouts, sensor/actuator faults). The vehicles are designed to detect the local environments by visual navigation and achieve a self-organisation formation. The robust fault-tolerant control strategy is investigated to deal with at least one network problem or physical failure. The effectiveness of the formation control strategy and its robustness should be verified by both simulations and experiments. Potential applications are in large flexibility MASs and high-security Cyber-Physical Systems.Currently, our lab is equipped with a multi-vehicle platform, consisting of quadrotors, ground robots and camera location systems. Algorithms are developed by either Matlab Code or C language. MATLAB, Simulink, OpenGL, Motive and Visual Studio are possiblesoftware to be chosen for this project.

Project team

Project students

• Abdul Rahim Mohammad
• Jie Yang
• Kamalpreet Singh
• Zirui Xie

Supervisors

• Prof. Peng Shi
• Prof. Cheng-Chew Lim

Advisors

• Xin Yuan
• Bing Yan
• Yuan Sun
• Yang Fei

Objectives

Design a robust formation control for multi-vehicle system to achieve:

• Self-decision making
• Environment detection
• Communication
• Obstacle avoidance
• Tolerance to physical or network problem

References

[1] Wooldridge, M (2002). An Introduction to MultiAgent Systems. John Wiley & Sons. ISBN 978-0-471-49691-5

[2] Balaji, P., & Srinivasan, D. (2010). An introduction to multi-agent systems. Studies in Computational Intelligence, 310, 1-27.

[3] Hong-Jun M., & Guang-Hong Y. (2016). Adaptive Fault Tolerant Control of Cooperative Heterogeneous Systems With Actuator Faults and Unreliable Interconnections. IEEE Transactions on Automatic Control, 61(11), 3240-3255.

[4] Oh k, Park M, & Ahn H. (2015). A survey of multi-agent formation control. Automatica, 53, 424-440.

[5] Khatib, O. (1986). Real-Time Obstacle Avoidance for Manipulators and Mobile Robots. The International Journal of Robotics Research, 5(1), 90–98. https://doi.org/10.1177/027836498600500106

[6] Autonomous Ground Vehicles Self-Guided Formation Control https://github.com/vitsensei/Trionychid-Formation-Control