In this study, we introduce a new online robot navigation strategy that exclusively utilizes discrete waypoints, steering a robot with the capability to proficiently address two critical tasks: path-following, even along self-intersected paths, and pursuing a moving target at a predefined distance within a two-dimensional (2-D) plane. First, the thin-plate spline (TPS) interpolation algorithm is employed to transform waypoints into an analytical continuous target curve. Subsequently, a comprehensive navigation framework that simultaneously considers computational cost and the upper bound of interpolation errors is proposed. This framework has the capability to generate time-varying guidance vector fields (GVFs) as guidance signals, which facilitates the robot to smoothly converge to the target curve. Furthermore, the GVF can be extended to accomplish collision-free navigation in cluttered environments. Experimental results demonstrate the effectiveness of our proposed approach in real-flight scenarios.

中文翻译：

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通过时变引导向量场使用离散路径点的在线机器人导航


在这项研究中，我们引入了一种新的在线机器人导航策略，该策略专门利用离散路径点，引导机器人能够熟练地解决两个关键任务：路径跟踪，甚至沿着自相交的路径，以及以预定义的速度追踪移动目标二维 (2-D) 平面内的距离。首先，采用薄板样条（TPS）插值算法将航路点转换为解析的连续目标曲线。随后，提出了一种同时考虑计算成本和插值误差上限的综合导航框架。该框架能够生成时变引导矢量场（GVF）作为引导信号，这有助于机器人平滑地收敛到目标曲线。此外，GVF 可以扩展以在杂乱环境中实现无碰撞导航。实验结果证明了我们提出的方法在真实飞行场景中的有效性。