多无人机协同吊运重物,实现复杂环境下的安全敏捷运输
Safe and Agile Transportation of Cable-Suspended Payload via Multiple Aerial Robots
- 基于完整运动约束与动力耦合建模,构建平滑轨迹生成框架
- 无需测量吊挂物状态,实现实时安全轨迹规划与精准跟踪
- 三机系统实测验证,对质量误差和非点质量鲁棒
使用多架空中机器人(MARs)协同运输重物可显著提升单个机器人的负载能力。然而,现有多架空中机器人运输系统(MARTS)仍难以在实时生成无碰撞、动力学可行且敏捷的轨迹,尤其在缺乏吊挂物与缆绳状态感知的情况下。为此,本文提出完整的规划与控制方案,实现复杂环境下安全敏捷的空中运输(SAAT)。通过考虑完整的运动学约束及各机器人与负载间的动力学耦合,推导出可用于轨迹生成的平坦度映射。为提升在复杂环境中生成安全、动力可行且敏捷轨迹的响应速度,提出一种实时时空轨迹规划方法。此外,摆脱对负载与缆绳状态测量及闭环控制的依赖,提出完全分布式控制方案,有效应对负载质量不精确与非点质量负载问题。通过基准对比、消融实验与仿真验证方案有效性。最终,在搭载机载计算机与传感器的三机MARTS系统上开展大量真实世界实验,结果证实所提方案在复杂环境中的高效性与鲁棒性。
原文摘要 · Abstract (English)
Transporting a heavy payload using multiple aerial robots (MARs) is an efficient manner to extend the load capacity of a single aerial robot. However, existing schemes for the multiple aerial robots transportation system (MARTS) still lack the capability to generate a collision-free and dynamically feasible trajectory in real-time and further track an agile trajectory especially when there are no sensors available to measure the states of payload and cable. Therefore, they are limited to low-agility transportation in simple environments. To bridge the gap, we propose complete planning and control schemes for the MARTS, achieving safe and agile aerial transportation (SAAT) of a cable-suspended payload in complex environments. Flatness maps for the aerial robot considering the complete kinematical constraint and the dynamical coupling between each aerial robot and payload are derived. To improve the responsiveness for the generation of the safe, dynamically feasible, and agile trajectory in complex environments, a real-time spatio-temporal trajectory planning scheme is proposed for the MARTS. Besides, we break away from the reliance on the state measurement for both the payload and cable, as well as the closed-loop control for the payload, and propose a fully distributed control scheme to track the agile trajectory that is robust against imprecise payload mass and non-point mass payload. The proposed schemes are extensively validated through benchmark comparisons, ablation studies, and simulations. Finally, extensive real-world experiments are conducted on a MARTS integrated by three aerial robots with onboard computers and sensors. The result validates the efficiency and robustness of our proposed schemes for SAAT in complex environments.
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