Target-tracking control method for autonomous vehicles based on hyperbolic-tangent line-of-sight guidance and odometry error compensation
Xiaosong Liu, Huanhai Zhu, Zebiao Shan, Qingsong Lu, Liben He
TL;DR
This paper introduces a new control method for autonomous vehicles that improves tracking accuracy using odometry and error compensation, even in complex environments.
Contribution
A novel target-tracking control method using hyperbolic-tangent line-of-sight guidance and odometry error compensation is proposed.
Findings
The proposed method reduced average position tracking error by 45.39% compared to ET-Fuzzy-MPC under complex road conditions.
Tracking error remained stable within 0.192 m during practical curved-path tests, showing improved accuracy and performance.
Abstract
The target-tracking accuracy of autonomous vehicles is closely related to that of onboard sensors. Methods such as image processing and base station positioning are susceptible to various types of interference in real-world scenarios, resulting in sensor data errors or even losses that ultimately affect the tracking accuracy of autonomous vehicles. This study proposes a target-tracking control method that relies solely on wheel odometry to address this issue. This method incorporates an extended state observer to compensate for the cumulative errors generated by the odometry mechanism, effectively enhancing the robustness and accuracy of the system in complex environments. In addition, a hyperbolic-tangent line-of-sight guidance strategy based on a partition-switching mechanism is designed to improve the dynamic response capability of an autonomous vehicle. This strategy nonlinearly…
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Taxonomy
TopicsControl and Dynamics of Mobile Robots · Robotic Path Planning Algorithms · Adaptive Control of Nonlinear Systems