Development of Swarm Robotics System Based on AI-Based Algorithms

In the recent past, swarm robotics technology has been widely applied in the variegated industrial domains. It essentially incorporates the multi-robot system with robots communicating with each other. In this work, a swarm of 30 robots is considered for warehouse management applications. A particle swarm optimization (PSO)-based swarm robotics system is manually designed and then simulated. The goal of the swarm is to employ the particle swarm optimization technique to efficiently complete loading and unloading duties in a warehouse. The swarm of robots that communicate with one another via radio frequency (RF) communication is subjected to particle swarm optimization. The physical prototype is built with two robot system equipped with sensors such as infra-red (IR), ultrasonic; motor drivers and RF communication unit. The major purpose of this project is to replace conventional approaches for finding the shortest path, such as the A* algorithm and Djikstra algorithm, with particle swarm optimization in order to load and unload items quickly and without the involvement of people. The physical prototype with sensors and RF communication demonstrates the feasibility of the proposed approach and provides a basis for further experimentation and improvement. Further research and experimentation are necessary to address the challenges and limitations of swarm robotics in warehouse management.