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.

翻译：协同运输作为物流信息物理系统（CPS）的关键环节，通常采用分布式控制与基于优化的方法进行处理。分布式控制方法耗时较少，但对多约束的处理与扩展能力较差。相反，基于优化的方法能有效处理约束，但通常采用集中式架构、计算耗时，因此难以扩展至大规模机器人集群。为克服两类方法的缺陷，本文通过改进传统编队控制，提出一种面向非完整移动机器人的新型协同运输方法。该方法具有分布式、低时间复杂度且能适应可扩展约束的特点。所提出的基于控制的方法在缆索悬吊载荷场景中得到验证，并分为机器人轨迹生成与轨迹跟踪两部分。与大多数耗时的轨迹生成方法不同，本方法仅需常数时间复杂度即可生成轨迹，且无需全局地图。在轨迹跟踪方面，本基于控制的方法不仅能像基于优化的方法那样轻松扩展至多约束场景，更将其时间复杂度从多项式级降至线性级。仿真与实验验证了本方法的可行性。