提出低复杂度协作运输方法，让多移动机器人高效运载悬吊负载。
Low-Complexity Cooperative Payload Transportation for Nonholonomic Mobile Robots Under Scalable Constraints
- 基于改进的编队控制，分布式执行且无需全局地图
- 轨迹生成仅需常数时间复杂度，轨迹跟踪复杂度从多项式降至线性
- 适合大规模非完整移动机器人系统，兼顾效率与约束扩展性
协作运输是物流网络物理系统（CPS）的关键环节，通常采用分布式控制或基于优化的方法。分布式方法计算快，但难以处理和扩展多个约束；优化方法能有效应对约束，但通常为集中式，耗时长，难以扩展至大量机器人。为此，本文提出一种针对非完整移动机器人的新型协作运输方法，通过改进传统编队控制，实现分布式、低时间复杂度，并支持可扩展约束。该方法分为轨迹生成与轨迹跟踪两部分：轨迹生成仅需常数时间复杂度，无需全局地图；轨迹跟踪在保持优化方法约束处理能力的同时，将时间复杂度从多项式降至线性。仿真与实验验证了方法的可行性。
原文摘要 · Abstract (English)
Cooperative transportation, a key aspect of logistics cyber-physical systems (CPS), is typically approached using dis tributed control and optimization-based methods. The distributed control methods consume less time, but poorly handle and extend to multiple constraints. Instead, optimization-based methods handle constraints effectively, but they are usually centralized, time-consuming and thus not easily scalable to numerous robots. To overcome drawbacks of both, we propose a novel cooperative transportation method for nonholonomic mobile robots by im proving conventional formation control, which is distributed, has a low time-complexity and accommodates scalable constraints. The proposed control-based method is testified on a cable suspended payload and divided into two parts, including robot trajectory generation and trajectory tracking. Unlike most time consuming trajectory generation methods, ours can generate trajectories with only constant time-complexity, needless of global maps. As for trajectory tracking, our control-based method not only scales easily to multiple constraints as those optimization based methods, but reduces their time-complexity from poly nomial to linear. Simulations and experiments can verify the feasibility of our method.
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