Nonholonomic Motion Control of Four-Wheeled Mobile Robot

The optimal motion planning problem of four wheeled mobile robot systems, due to the nonholonomic constraints, is usually transformed into an optimal control problem of nonlinear system. The ameliorated genetic algorithm of optimal control for motion planning is presented with encoding the optimized variables with float-point number. The strategy the best individual to be reserved in the ameliorated genetic algorithm operation is applied. With appropriate crossover parameter and self-adaptive aberrance factor, the convergence of the algorithm is improved and the system's motion precision is leveraged. The numerical simulation indicates the effectiveness of the algorithm for motion control of four wheeled mobile robot systems.