A new path following algorithm with uncertainty information of robot's initial position and its implementation
Jinke Li, Ruiqing Fu, Xinyu Wu, Jianquan Sun, Huiwen Guo, Shaomin Zhang · 2015
In recent years, researchers come up with lots of path following algorithms. One of their basic assumptions is that the robot's initial position is a single certain point. Actually, as robots rely on sensor data to locate by Kalman filter or Partical filter, it outputs a probability distribution. In this paper, F* describes a new path following algorithm with the robot's initial position is uncertain. It depends on Monte Carlo method and A* algorithm. Some important concepts are introduced and pseudo code is given to show how it works. Experiment results show that it is more effective than general algorithm.