Coordination of multi-robot path planning for warehouse application using smart approach for identifying destinations

Abstract

Path planning and coordination in a multi-robot system are important and complex tasks in any environment. In a multi-robot system, there can be multiple objectives to be achieved by multiple robots simultaneously. Nowadays, many mobile service robots are being used in warehouses to reduce running costs and overheads. In a large warehouse, there can be multiple robots to handle the number of operations. Planning a path means to find out the optimal route, and coordinating them means a collision-free route. To get both the parameters to reach their optimal level becomes a tedious task to achieve. The efficiency of overall warehouse operation can be improved by adequately addressing the coordination and path planning issues among the robots. In warehouses, each robot has to navigate to its destination by finding a collision-free optimal route in coordination with other robots. In this paper, a comparative study with the acclaimed path planning and coordination has been presented. The proposed smart approach has been presented for a multi-robot system to find a collision-free optimal path in a warehouse to handle storage pods. This paper proposes a smart distance metric-based approach for a multi-robot system to identify their goals smartly and traverse only a minimal path to reach their goal without getting being collided. It uses a smart distance metric-based approach to find the intended path. The proposed work performs better when compared with other works like A* and ILP. It is strictly monitored that there is no collision occurred during execution. Three different instances of a warehouse have been considered to carry out the experiments with parameters such as path length, average path and elapsed time. The experiments with 800 pods and 16 robots report the improvement in performance up to 2.5% and 13% in average path length and elapsed time.