Mobile Robot Static Path Planning Based on Genetic Simulated Annealing Algorithm

Robot path planning in a static environment is studied and Genetic Simulated Annealing is proposed. In the genetic algorithm, large-scale initialization combined with the selecting mechanism is applied to initialize the starting point out of the barrier area. A simple real one-dimensional coding technique is used; The feasibility, smoothness and length of a path determine an efficient adaptive function,and an effective genetic operators is set up. In the simulated annealing, random moving rule uses Metropolis rule and devise efficient temperature update function. The simulation result confirms that the genetic simulated annealing algorithm is feasible and efficient for mobile robot path-planning.