Optimization design of mobile robot based on genetic algorithm

PID controller parameters of mobile robot are optimized based on genetic algorithm aiming at the control requirements for position and speed of mobile robot. The performance index for the integral of time-weighted absolute error is used as the minimum objective function during parameter choice, and the optimal solution to the global optimization in the no prior knowledge condition could be obtained by making use of the global search capability of genetic algorithm in order to reduce difficulty in the PID parameter adjusting and to improve the accuracy and robustness of the system. Aimed at the unknown and dynamic environment path planning problem of the mobile robot, mobile robot system is designed, dynamic grid is used to make environmental modeling, on the basis of the traditional genetic algorithm definite improvement, and individual evaluation function may take feasible path fitness function and not feasible path fitness function separately. The algorithm design and simulation indicate that the method is used to the dynamic path planning of mobile robot, not with any barrier collision, path short and planning curve smoothing, satisfactory results and planning convergence rate are achieved.