Path planning is necessary for mobile robots to perform precise and rapid tasks. A collision avoidance function must be included so that the robot can move safely during work, and it must be able to create an optimal path to reduce work execution time and save energy. In this paper, we propose a smart route generation algorithm that searches for global route with an algorithm that can speed up route search and integrates the TEB algorithm that can search for regional optimum routes in real time according to the situation. The performance of the proposed algorithm was verified through actual driving experiments of mobile robots.

Path planing method for an autonomous mobile robot is considered. For the practical applications, the simplified local potential field methods are applied under the constraints of the driving condition. To improve the performance, the fuzzy-approximated linear function method is also used.