新型自适应阻抗控制提升人机协同吊运效率与安全性
Task-Adaptive Admittance Control for Human-Quadrotor Cooperative Load Transportation with Dynamic Cable-Length Regulation

- 基于可调缆长的无人机-人协同吊运自适应控制
- 动态调节缆长使系统响应更快、运动更平滑
- 适合需人机物理交互的复杂吊运任务
人机协作在众多机器人应用中至关重要,尤其在需要物理人机交互(pHRI)的场景。以往研究多集中于机械臂,采用阻抗或导纳控制保障操作安全。而人-无人机协同吊运(CLT)研究仍处于初期阶段。本文提出一种新型导纳控制器,用于配备主动控制绞盘的无人机,在人-无人机协同吊运中实现安全高效作业。该方法考虑系统耦合动力学特性,使无人机与缆绳能动态适应接触力,提升响应性。实验验证了控制器在完整吊运流程中的任务自适应能力,包括原地装卸与运输任务。对比传统方法,分别在可变与固定缆长、低刚度与高刚度条件下进行测试。结果表明,所提方法在系统响应性和运动平滑性上均优于传统方案,显著提升吊运性能。
原文摘要 · Abstract (English)
The collaboration between humans and robots is critical in many robotic applications, especially in those requiring physical human-robot interaction (pHRI). Previous research in pHRI has largely focused on robotic manipulators, employing impedance or admittance control to maintain operational safety. Conversely, research in human-quadrotor cooperative load transportation (CLT) is still in its infancy. This letter introduces a novel admittance controller designed for safe and effective human-quadrotor CLT using a quadrotor equipped with an actively-controlled winch. The proposed method accounts for the system's coupled dynamics, allowing the quadrotor and its cable to dynamically adapt to contact forces during CLT tasks, thereby enhancing responsiveness. We experimentally validated the task-adaptive capability of the controller across the entire CLT process, including in-place loading/unloading and load transporting tasks. To this end, we compared the system performances against a conventional approach, using both variable and fixed cable lengths under low- and high-stiffness conditions. Results demonstrate that the proposed method outperforms the conventional approach in terms of system responsiveness and motion smoothness, leading to improved CLT capabilities.
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