The research on robot path planning with multi-constrains

According to the realistic duty of robot, it´s necessary to find a short path to avoid obstacles and carry limited goods, and then the added constrains let the problem is more complex and more practical. The paper proposes a tabu-genetic algorithm for robot path planning. By utilizing the main frame of parallel search supplied by genetic algorithm and embed the individual serial search mode of tabu search algorithm, this method can enlarge search space. And in order to enhance optimized speed and quality, also improve the algorithm performance, fitness function and amendatory policy are designed. Besides, algorithm convergence is analyzed based on the model of Markov chains. The results of simulations show that the method proposed in this paper, which can find an optimal path quickly and improve convergence speed and solution quality greatly.