A novel swarm robot simulation platform for warehousing logistics

Abstract

Swarm robot systems are widely applied in the warehouse logistics, which effectively improve logistics efficiency. Task allocation is the core problem for swarm robot systems. Therefore, evaluation of the task allocation strategy has very important practical significance. However, current simulation platforms, such as GAZEBO, require a lot of setup work before testifying the task allocation strategy for various applications. Regarding warehousing logistics, a few special factors need to be considered: man-robot coexistence in working environment, the energy consumption of robots and collision avoidance among robots. Therefore, we propose a novel swarm robot simulation platform, called MultiBots, based on multi-agent pathfinding (MAPF) method and collision avoidance strategy, which can correctly evaluate the effectiveness of task allocation strategy. Moreover, we design the charging process to supplement the energy consumption of robots. The experimental results show that the proposed MultiBots satisfies the requirements of task allocation strategy evaluation in warehouse logistics scenarios. The MultiBots can be applied in testifying the efficiency of task allocation strategy for logistics systems.