为移动机器人设计统一控制框架，实现轨迹跟踪与动态避障。
Sliding Mode Control for Safe Trajectory Tracking with Moving Obstacles Avoidance: Experimental Validation on Planar Robots
- 通过广义运动学变换将多种机器人模型转为严格反馈形式
- 实验证明在扰动下仍能渐近跟踪轨迹并严格避障
- 首次应用于阿克曼转向车，适合多类地面飞行机器人
本文提出一种统一控制框架，适用于广泛类型的移动机器人，实现鲁棒轨迹跟踪与动态障碍物避让。通过构建广义运动学变换，将多种车辆动力学转化为严格反馈形式，便于设计滑模控制策略以实现精确、鲁棒的参考轨迹跟踪。为确保动态环境中的操作安全，将跟踪控制器与基于碰撞锥控制屏障函数（C3BF）的安全过滤器集成。所提架构在外部干扰存在时保证渐近跟踪，并严格满足碰撞避免约束。该工作的创新在于首次为阿克曼转向型地面机器人设计滑模控制器。方法的有效性与通用性通过数值仿真及三类平台的大量真实实验验证：阿克曼转向车辆、差速驱动机器人和四旋翼无人机。实验视频见 https://youtu.be/dWcxwum96vk
原文摘要 · Abstract (English)
This paper presents a unified control framework for robust trajectory tracking and moving obstacle avoidance applicable to a broad class of mobile robots. By formulating a generalized kinematic transformation, we convert diverse vehicle dynamics into a strict feedback form, facilitating the design of a Sliding Mode Control (SMC) strategy for precise and robust reference tracking. To ensure operational safety in dynamic environments, the tracking controller is integrated with a Collision Cone Control Barrier Function (C3BF) based safety filter. The proposed architecture guarantees asymptotic tracking in the presence of external disturbances while strictly enforcing collision avoidance constraints. The novelty of this work lies in designing a sliding mode controller for ground robots like the Ackermann drive, which has not been done before. The efficacy and versatility of the approach are validated through numerical simulations and extensive real-world experiments on three distinct platforms: an Ackermann-steered vehicle, a differential drive robot, and a quadrotor drone. Video of the experiments are available at https://youtu.be/dWcxwum96vk
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