Path planning of food sorting robot based on improved chicken swarm optimization algorithm

Abstract

Objective: In order to improve the efficiency of path optimization of multi station food sorting robot, a path planning scheme of food sorting robot based on improved chicken swarm optimization algorithm is proposed. Methods: The two-level path planning model of multi station food sorting robot was constructed by fully consider the optimal picking position of the robot at a single station and the shortest moving distance of the robot between multiple stations. The improved chicken swarm optimization （ICSO） algorithm was designed. The density peak clustering algorithm was used to cluster the population of ICSO, and the individual coding mode and the evolution update mechanism were redefined. Finally the ICSO was used to solve the double-layer model of path planning, so as to solve the shortest path of food sorting and robot movement. Results: Compared with other path planning methods, the total path was shortened by 7.3%~16.7% and the running time was reduced by 8.14%~39.33%. Conclusion: The proposed scheme improves the path planning efficiency of food sorting robot and has good practical application value.

Keywords

• food sorting
• mobile robot
• route planning
• chicken swarm optimization algorithm