Path Planning of Omnidirectional Mobile Vehicle Based on Road Condition

This paper concerns with the vehicle path planning problem considering the actual natural environment and social environment, which may influence the reliability and stability. The basic path planning problem is determined to solve the optimal path problem. In here, the surface properties and terrain has been taken into consideration, based on improved ant colony algorithm(ACA). Unlike the assumptions of basic ACA, in this case the terrain slope and the surface condition are analyzed and described in order to set up terrain table and vehicle capacity table. Therefore, coordinating the terrain and the obstacles condition, the reliability is enhanced. For instance, this paper optimizes the initial pheromone distribution, path point selection strategy, pheromone updating method, upon the shortage of basic ACA, such as low initial search speed, poor convergence, the problem of local optimum. Eventually, the results of simulation are exhibited, which shows the model and algorithm's efficiency.