Low-Complexity Cooperative Payload Transportation for Nonholonomic Mobile Robots Under Scalable Constraints

--Cooperative transportation, a key aspect of logistics cyber-physical systems (CPS), is typically approached using distributed 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. T o overcome drawbacks of both, we propose a novel cooperative transportation method for nonholonomic mobile robots by improving 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 polynomial to linear . Simulations and experiments can verify the feasibility of our method. ECENTL Y, logistics cyber-physical systems (CPS), particularly multi-robot cooperative transportation, have garnered increasing attention due to their advantages, such as cost reduction and enhanced productivity [1]-[17]. In this scenario, robots are required to coordinately transport the payload from a starting place to the desired destination quickly. Typically, the robot formation is subject to numerous constraints in practical transportation, such as obstacle avoidance, inter-robot collision avoidance, velocity constraints, payload protection, nonholonomic kinematics, etc. So far, how to overcome as many constraints as possible in the shortest time has become an important issue in cooperative transportation problems. Most cooperative transportation algorithms are based on two frameworks, including distributed control [3]-[8] and optimization [10]-[17].