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Title: Vision-based flexible leader-follower formation tracking of multiple nonholonomic mobile robots in unknown obstacle environments
Authors: Wang, Yuanzhe
Shan, Mao
Yue, Yufeng
Wang, Danwei
Keywords: Flexible Formation
Formation Control
DRNTU::Engineering::Electrical and electronic engineering
Issue Date: 2019
Source: Wang, Y., Shan, M., Yue, Y., & Wang, D. Vision-based flexible leader-follower formation tracking of multiple nonholonomic mobile robots in unknown obstacle environments. IEEE Transactions on Control Systems Technology, 1-9. doi:10.1109/TCST.2019.2892031
Series/Report no.: IEEE Transactions on Control Systems Technology
Abstract: This brief investigates the flexible leader-follower formation tracking problem for a group of nonholonomic mobile robots, while most of the formation control related work in the literature focuses on the rigid formation. The flexible formation discussed in this brief is defined in curvilinear coordinates in terms of longitudinal separations between robots along the reference trajectory and lateral deviations with respect to this trajectory. Unlike the previous studies on flexible formation control, this brief is under a more challenging assumption that the global position and orientation measurements are not available. To obtain the relative pose relationships amongst robots, a stereo camera is mounted on each follower. In consideration of the fact that visual observations are noise-corrupted and intermittently available, a particle filter-based relative pose estimation approach is employed to estimate the position and orientation of the leader in the local reference frame of the follower using the polluted and discontinuous information. Also, to form a flexible formation, the leader historical trajectory is reconstructed with respect to the current local frame attached on the follower, based on which a reference point is generated. In addition, this brief considers the situation where robots operate in unknown obstacle environments. To ensure robot safety in such environments, a multiobjective control law is proposed to balance reference tracking and collision avoidance in different situations. Simulation and real-robot experiment have been performed to demonstrate the efficacy of the proposed method.
ISSN: 1063-6536
DOI: 10.1109/TCST.2019.2892031
Schools: School of Electrical and Electronic Engineering 
Rights: © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at:
Fulltext Permission: open
Fulltext Availability: With Fulltext
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