Regular Paper

International Journal of Control, Automation and Systems 2019; 17(9): 2297-2309

Published online May 27, 2019

https://doi.org/10.1007/s12555-019-0006-8

© The International Journal of Control, Automation, and Systems

Adaptive Trajectory Tracking of Wheeled Mobile Robots Based on a Fisheye Camera

Zhaobing Kang, Wei Zou*, Hongxuan Ma, and Zheng Zhu

Chinese Academy of Sciences

Abstract

This paper presents a novel adaptive trajectory tracking control method, which can precisely control wheeled mobile robots only using an uncalibrated fish-eye camera fixed on the ceiling. Different from existing approaches, the inertial device, distorted image correction, and the trajectory expression are not required in the control system. The position and orientation of the mobile robot in the camera coordinate system are estimated by the extended POSIT (Pose from Orthography and Scaling with Iteration) algorithm in real-time. Based on estimation results, the controller considering both tracking errors and parameter estimated errors is designed by linear parameterization, where the camera intrinsic parameters are online updated. The asymptotic convergence of the tracking error and the estimated error to zero is proved by the Barbalat lemma. Circular trajectory and irregular trajectory tracking experiments have been conducted to verify the performance of our controller.

Keywords Adaptive control, pose estimation, visual trajectory tracking, wheeled mobile robots.

Article

Regular Paper

International Journal of Control, Automation and Systems 2019; 17(9): 2297-2309

Published online September 1, 2019 https://doi.org/10.1007/s12555-019-0006-8

Copyright © The International Journal of Control, Automation, and Systems.

Adaptive Trajectory Tracking of Wheeled Mobile Robots Based on a Fisheye Camera

Zhaobing Kang, Wei Zou*, Hongxuan Ma, and Zheng Zhu

Chinese Academy of Sciences

Abstract

This paper presents a novel adaptive trajectory tracking control method, which can precisely control wheeled mobile robots only using an uncalibrated fish-eye camera fixed on the ceiling. Different from existing approaches, the inertial device, distorted image correction, and the trajectory expression are not required in the control system. The position and orientation of the mobile robot in the camera coordinate system are estimated by the extended POSIT (Pose from Orthography and Scaling with Iteration) algorithm in real-time. Based on estimation results, the controller considering both tracking errors and parameter estimated errors is designed by linear parameterization, where the camera intrinsic parameters are online updated. The asymptotic convergence of the tracking error and the estimated error to zero is proved by the Barbalat lemma. Circular trajectory and irregular trajectory tracking experiments have been conducted to verify the performance of our controller.

Keywords: Adaptive control, pose estimation, visual trajectory tracking, wheeled mobile robots.

IJCAS
March 2025

Vol. 23, No. 3, pp. 683~972

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