Path Following of Wheeled Mobile Robots Using Online-Optimization-Based Guidance Vector Field
Path Following of Wheeled Mobile Robots Using Online-Optimization-Based Guidance Vector Field
复制标题
使用基于在线优化的制导向量场的轮式移动机器人路径跟踪
DOI：
10.1109/tmech.2021.3077911
复制
发表时间：
2021-08-01
影响因子：
6.4
通讯作者：
Wang, Yuexuan
中科院分区：
文献类型：
--
作者：
Chen, Jian;Wu, Chengshuai;Wang, Yuexuan
研究了非完整约束轮式移动机器人的路径跟踪问题。将路径跟踪任务表示为制导向量场，并采用在线优化方法估计路径误差。通过利用基于矩阵测量的压缩原理，从理论上保证了所设计的GVF关于任务路径的收敛性质。然后，设计了一个非线性控制器来跟踪所定义的GVF，使得受控移动机器人在存在未知扰动的情况下跟踪目标路径，包括未建模的动力学和表面摩擦。分析了闭环系统的鲁棒性，证明了路径误差最终收敛到残差集合，可以通过增加控制增益来减小残差集合。通过实验验证了所设计的GVF和所提出的控制设计的有效性。
This article studies a path-following problem for a wheeled mobile robot with nonholonomic constraints. The path-following task is represented by a guidance vector field (GVF), for which an online optimization procedure is adopted to estimate the path error. By exploiting a matrix-measure-based contraction principle, the convergence property of the designed GVF with respect to the task path is theoretically guaranteed. Then, a nonlinear controller is developed to track the defined GVF such that the target path is followed by the controlled mobile robot in the presence of unknown disturbances, including the unmodeled dynamics and the surface friction. Robustness properties of the closed-loop system are analyzed, and it is shown that the path error eventually converges to a residual set, which can be reduced by increasing control gains. Experiments are provided to validate the effectiveness of the desired GVF and the proposed control design.