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Research on an Optimization Algorithm for Robot Automatic Control and Path Planning
Fenggang Liu, Guobiao Fei and Xiao Li

This paper briefly introduced the automatic control principle of mobile robots. Then, The traditional genetic algorithm was improved by co-evolution. Finally, the simulation experiment was carried out on the improved and non-improved genetic algorithms in MATLAB software. The real movement test was carried out on the robot before and after the improvement. The simulation results showed that the improved genetic algorithm converged to stability faster and planned a shorter path with fewer turning points. The real movement test results suggested that the improved genetic algorithm could make the mobile robot plan shorter paths that cost less movement time and avoided more collisions in the movement process under automatic control.

Keywords: robot, automatic control, route planning, genetic algorithm

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