Research On Path Planning Method For Mobile Robot

Path planning of mobile robot is the most important part in the mobile robot navigation system. It is worthy to pay attention to the problem how to effectively avoid obstacles while planning out the least costly path to guide the robot to move. The global path planning can plan out the least costly path to avoid obstacles in the premise. This research studies the problem of mobile robot path planning method, using the digital processing technology to access to environmental information,giving a new solution to the problem of path planning of mobile robot called magnetic bacteria optimized algorithm, which showed great advantage in terms of the stability of the search path and convergence time.The main contents are as follows:1. Before the route search, the most important thing is accessing to environmental information and information processing. In terms of environmental information acquisition,processing the collected images of the camera, and then get the edges of the obstacles, and then load to the grid diagram according to the aspect ratio. In addition, considering the safety of the actual path, adopting the method of virtual obstacles after the robot is considered as a particle, viz, expand the obstacle information in grid diagram with the radius of the robot. The method can make the robot successfully avoid obstacles when moves along the planned route.2. After environmental modeling, this article focuses on two algorithms of the search for the path, viz, biogeography algorithm and magnetic bacteria optimization algorithm.According to the problems of biogeography algorithm (BBO) during the search, taboo mobile strategy is proposed and migration strategy is modified. The simulation experiments confirmed that the improved algorithm can not only shorten the path, but also improve the convergence speed and reduce the planning of aging.3. For the magnetic bacteria algorithm (MBOA), this paper studies the effects of the number of cells, the magnetic induction and two energy coefficient, and a certain scope is given according to simulation results. Combined with actual situation, the virtual barrier method is proposed to ensure the safety of the route and use Bezier curve to improve the smoothness of the path.4. In this chapter, we compare the four algorithms of BBO, MBOA, PSO and A*. In order to fully compare the performance of the algorithm, simulation experiments were carried out in the known and unknown environment of elementary complexity, medium complexity and high complexity respectively and evaluate the stability of the algorithm and the time of planning by statistical relevant theories. Finally, according to the condition of the path to be met in the actual situation, the general evaluation function is proposed, which is composed of the security penalty function and the shortest path penalty function.