Real-time Path Planning for Mobile Robots Based on Quantum Evolutionary Algorithm

Abstract

In order to solve the problem of real-time path planning for mobile robots,an improved quantum evolutionary algorithm was proposed.By using the grid method to build the environment model,a novel decoding method which transforms the quantum individual into the path described by grid points was presented.On the basis of the quantum rotation gate,the cross and mutation operator in genetic algorithm and a repair operation specifically designed for the path planning problem were introduced to update the quantum population together,which improved the searching efficiency.With the help of GUI in Matlab,process of the robot real-time path planning was simulated.Simulation results indicate that the proposed method can obtain a feasible and short path in the complex environment.Additionally,when a new obstacle appears suddenly,or the original ones move towards different directions,this method can also response quickly and replan an optimal path in the new environment.