Multi-robot Coordination for a Heterogeneous Fleet of Robots

Abstract

There is an increasing need for autonomous mobile robots (AMRs) in industrial environments. The capability of autonomous movement and transportation of items in industrial environments provides a significant increase in productivity and efficiency. This need, coupled with the possibility of controlling groups of heterogeneous robots, simultaneously addresses a wide range of tasks with different characteristics in the same environment, further increasing productivity and efficiency. This paper will present an implementation of a system capable of coordinating a fleet of heterogeneous robots with robustness. The implemented system must be able to plan a safe and efficient path for these different robots. To achieve this task, the TEA* (Time Enhanced A*) graph search algorithm will be used to coordinate the paths of the robots, along with a graph decomposition module that will be used to improve the efficiency and safety of this system. The project was implemented using the ROS framework and the Stage simulator. Results validate the proposed approach since the system was able to coordinate a fleet of robots in various different tests efficiently and safely, given the heterogeneity of the robots.

State of the Art in Robot Fleet Management: From Task Allocation to Motion Planning

“…There also further variations that add a layer to the A* algorithm in order to consider neighbor cells in further steps (Time Enhanced A*) (Pereira et al, 2023). Hence it is possible to work on dynamic scenarios, but the collision avoidance is still performed with stop and go.…”