Control Barrier Function Based Adaptive Tracking of a Mobile Robot under Field of View Constraints

• Published in: Chinese Control Conference pp. 4681 - 4686
• Main Authors: Liu, Yehui, Shen, Jiajun, Ma, Mingxiao, Bai, Zitong, Wang, Wei
• Format: Conference Proceeding
• Language: English
• Published: Technical Committee on Control Theory, Chinese Association of Automation 28.07.2024
• Subjects: Adaptation models; Adaptive Control; Control Barrier Function; Control design; Estimation error; Field of View; Mobile Robot; Parameter estimation; Robot vision systems; Sensors; Tracking Control; Visualization
• ISSN: 1934-1768
• DOI: 10.23919/CCC63176.2024.10662702

The paper focuses on adaptive tracking control of a mobile robot with uncertain dynamic models and visibility constraints. An onboard visual RGB-D camera that provides the relative distance and bearing angle is subject to field of view (FOV) due to sensing capabilities. Furthermore, the field of view constraints potentially conflict with tracking task. To address these problems, the tracking task and the FOV constraints can be transformed to control Lyapunov functions (CLFs) and control barrier functions (CBFs), respectively. Then a controller is proposed by combining the CLF and CBF via quadratic programming (QP). A novel adaptive parameter estimation method with projector operator is provided such that estimation errors can be kept within a small neighborhood of the origin. This control design based on QP and parameter updates enables the fulfillment of the tracking task while satisfying the FOV constraints. The proposed adaptive tracking scheme is validated through physical experiments.