Probabilistic Trajectory Estimation based Leader Following for Multi-Robot Systems

• Main Authors: Shan, Mao, Zou, Ying, Guan, Mingyang, Wen, Changyun, Lim, Kwang-Yong, Ng, Cheng-Leong, Tan, Paul
• Other Authors: School of Electrical and Electronic Engineering
• Format: Conference or Workshop Item
• Language: English
• Published: 2017
• Subjects: trajectory control; multi-robot systems
• Online Access: https://hdl.handle.net/10356/82415; http://hdl.handle.net/10220/42306
• Institution: Nanyang Technological University

The paper is concerned with the multi-robot leader-following problem in the presence of frequent dropouts in vision detection. In many scenarios, for instance a structured environment, it is inevitable to experience outage of vision detection due to reasons such as the target moving out of view, vision occlusion, motion blurring, etc. The paper proposes a Bayesian trajectory estimation based leader-following approach that can offer accurate path following given intermittent vision observations. The follower robot estimates the trajectory of the leader robot based on the noise-corrupted odometry information of both robots, and inter-robot relative observations based on detection of fiducial markers using an RGBD camera. A linear trajectory-following control method is employed to track a historical pose of the leader robot on the estimated trajectory. Results are obtained based on evaluating the proposed leader-following approach in tests with a zig-zag shaped trajectory and with a trajectory that contains sharp turns.