Unity 3D-Based Simulation Data Driven Robotic Assembly Sequence Planning Using Genetic Algorithm

Abstract

Robotic assembly is an important way to realize manufacturing intelligence. In the robotic assembly process, assembly sequence planning helps to improve the assembly efficiency. However, the existing research around assembly sequence planning always used hypothetical data or random data to get the optimal solution and it is not suitable for robotic assembly process because it does not consider the characteristics of the industrial robots. Aiming at this, in this paper, Unity-3D based simulation data driven robotic assembly planning using genetic algorithm is proposed in order to solve robotic assembly planning problem. The feasible assembly sequence is obtained by graph-based assembly precedence model. After that, the improved genetic algorithm is proposed. In the meanwhile, Unity3D-based simulation is utilized to obtain the simulation data for robotic assembly process. Based on a camera, the performance of the improved genetic algorithm is analyzed and compared with the traditional genetic algorithm. It shows the proposed method is suitable for robotic assembly sequence planning problem.