Multi-objective Genetic algorithm for High-density Robotic workcell

This paper presents a scheduling problem for a high-density robotic workcell using multi-objective genetic algorithm. Multi-robots motions are coordinated to perform with efficiency under various working conditions in the limited area while avoiding collisions between the robots. We make the best use of genetic algorithm by adding multi-object for scheduling of the multi robot system. We simulate motion of six robots with the optimized schedule and show effectiveness of the proposed multi-objective genetic algorithm.This research was supported by the MSIP(Ministry of Science, ICT & Future Planning), Korea, under the CITRC(Convergence Information Technology Research Center) support program (NIPA-2013-H0401-13-1008) supervised by the NIPA(National IT Industry Promotion Agency) and Industrial Strategic technology development program, 10033555, Multi-Robots Process Optimization for High Density Manufacturing funded By the Ministry of Trade, industry & Energy(MI, Korea)