将逆运动学用于引导向量场,实现无人机精准路径跟踪
Inverse Kinematics on Guiding Vector Fields for Robot Path Following
- 用隐式方程定义路径,构建误差信号驱动机器人趋近路径
- 使路径误差呈线性系统行为,可精确控制过渡过程
- 在固定翼无人机上验证,实现2D路径的高精度动态跟踪
逆运动学是机器人运动与定位控制的基础技术,通常应用于末端执行器。本文将逆运动学概念拓展至引导向量场,用于自主移动机器人的路径跟踪。目标路径通过其隐式方程定义,即一个或多个零水平集上的点集。这些水平集作为参考,构建误差信号,驱动引导向量场趋近目标路径,使机器人沿该向量场收敛并行进。首先在m维欧氏空间中对单积分器机器人形式化阐述逆运动学在引导向量场中的应用;随后利用逆运动学确保水平集误差信号表现为线性系统,便于控制机器人向目标路径的瞬态运动,并支持前馈信号注入以实现路径上的精确运动行为。针对具有恒定速度的独轮车模型在二维路径上的实际应用,提出理论与实践挑战的解决方案。最后通过固定翼无人机的真实飞行实验验证了理论预测结果。
原文摘要 · Abstract (English)
Inverse kinematics is a fundamental technique for motion and positioning control in robotics, typically applied to end-effectors. In this paper, we extend the concept of inverse kinematics to guiding vector fields for path following in autonomous mobile robots. The desired path is defined by its implicit equation, i.e., by a collection of points belonging to one or more zero-level sets. These level sets serve as a reference to construct an error signal that drives the guiding vector field toward the desired path, enabling the robot to converge and travel along the path by following such a vector field. We start with the formal exposition on how inverse kinematics can be applied to guiding vector fields for single-integrator robots in an m-dimensional Euclidean space. Then, we leverage inverse kinematics to ensure that the level-set error signal behaves as a linear system, facilitating control over the robot's transient motion toward the desired path and allowing for the injection of feed-forward signals to induce precise motion behavior along the path. We then propose solutions to the theoretical and practical challenges of applying this technique to unicycles with constant speeds to follow 2D paths with precise transient control. We finish by validating the predicted theoretical results through real flights with fixed-wing drones.
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