Path and sensing point planning for mobile robot navigation to minimize the risk of collision

In this paper, a new path planning algorithm for mobile robotics is proposed. When a mobile robot is navigating, the error in estimated position of the robot increases in proportion to the traveling distance. Because of this error, the robot has a greater risk of collision with objects in the environment. To reduce this error, roobt should obtain environment information by using its environment sensors, and modify it's estimated position accordingly. In this paper, the cost function for the mobile robot's path which minimizes the risk of collision, and the algorithm to find the optimal path and sensing points are proposed. The authors implemented the proposed algorithm on real robot system, and made several experiments to verify this algorithm.