Collision Avoidance and Give Way of Heterogeneous and Variable-Sized Multiple Mobile Robots Based on Glued Nodes

Multiple mobile robot systems (MMRSs) play an important role in workshops, storage and other scenarios. A complex MMRS can contain heterogeneous robots, and even the robot sizes are not fixed, making it more difficult to avoid collisions. As a widely studied method, the zone-controlled method is not accurate enough for a system with heterogeneous and variable-sized robots, and it increases the difficulty of applying MMRS. Based on the concept of glued nodes, this paper proposes a more accurate calculation method than the zone-controlled method to avoid collisions among heterogeneous and variable-sized robots. In order to improve the efficiency of calculating glued nodes, this paper proposes a time-to-space method, which has a constant complexity after the system runs long enough. In addition to collision avoidance, this paper also studies the problem of giving way of idle robots. This paper proposes a method which can detect those idle robots blocking the working robots and plan paths for the idle robots to find avoidance nodes to give way to the working robots. Simulation experiments are carried out based on a real automated production line scenario, and the experimental results prove the effectiveness and efficiency of the proposed methods. Note to Practitioners—In a complex MMRS, the size of different robots can be different, and even the size of a robot is different when loaded and unloaded. One of the motivations of this paper is to avoid collisions in such a complex MMRS. A collision avoidance method is proposed to avoid collisions among robots by allocating nodes in real time. At the same time, this paper also addresses the problem of idle robots blocking working robots. If an idle robot blocks some working robots, an avoidance node will be found for the idle robot to give way to the working robots. The methods proposed in this paper can be applied to the roadmap of any structure. This means that in a scenario, regardless of the structure of roadmap and the different sizes of robots, the methods can be applied directly. The methods have been applied to many practical industrial projects in warehousing, manufacturing and other scenarios, and greatly reduces the difficulty of applying MMRS. In future research, there is a need to improve the efficiency of the methods so that they can be applied to a large-scale system.