让无人机机械臂在未知环境实时导航，轨迹更平滑安全。
RINGO: Real-time Navigation with a Guiding Trajectory for Aerial Manipulators in Unknown Environments
- 用预设飞行轨迹引导末端执行器规划，兼顾机身与机械臂位置。
- 生成的轨迹更平滑且不越界，比仅考虑机身的方案更激进。
- 首次实现未知环境中无人机机械臂的实时导航，适合智能机器人研发者。
在受限环境下对无人机机械臂进行运动规划通常局限于已知环境，或简化为多旋翼规划，导致适应性差且轨迹过于保守。本文提出 RINGO：基于引导轨迹的实时导航框架，使无人机机械臂能在未知环境中实时导航。该方法同时考虑多旋翼和末端执行器的位置，以预先获取的多旋翼轨迹作为引导参考，使末端执行器生成平滑、无碰撞且符合工作空间约束的轨迹。利用B样条曲线的凸包性质，理论上保证轨迹始终在可达工作空间内。据我们所知，这是首个实现无人机机械臂在未知环境中实时导航的工作。仿真与实验结果验证了该方法的有效性。相比仅考虑多旋翼的方法，本方法生成的轨迹更少保守。
原文摘要 · Abstract (English)
Motion planning for aerial manipulators in constrained environments has typically been limited to known environments or simplified to that of multi-rotors, which leads to poor adaptability and overly conservative trajectories. This paper presents RINGO: Real-time Navigation with a Guiding Trajectory, a novel planning framework that enables aerial manipulators to navigate unknown environments in real time. The proposed method simultaneously considers the positions of both the multi-rotor and the end-effector. A pre-obtained multi-rotor trajectory serves as a guiding reference, allowing the end-effector to generate a smooth, collision-free, and workspace-compatible trajectory. Leveraging the convex hull property of B-spline curves, we theoretically guarantee that the trajectory remains within the reachable workspace. To the best of our knowledge, this is the first work that enables real-time navigation of aerial manipulators in unknown environments. The simulation and experimental results show the effectiveness of the proposed method. The proposed method generates less conservative trajectories than approaches that consider only the multi-rotor.
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