Improved ant colony optimization based robot path planning

To solve the problems that ant colony algorithm often gets sub optimal solution, the turning angle is too large and the convergence effect is poor when planning the global path of the robot, the traditional ant colony algorithm is improved. The grid map is applied to construct the working surrounding, the path heuristic function is designed to enhance the searching ability and convergence effect of the algorithm. Considering the influence of turning Angle on travel time, the heuristic function of turning Angle is introduced to ensure the ant colony to have more guidance in the planning and make the path smoother. Pheromone updating rules and path evaluation mechanism are established to guide ants to approach the path with the best comprehensive index. The algorithm is simulated on the MATLAB platform, the simulation indicates that the optimized algorithm has good convergence effect and strong optimization ability.