부산대학교 도서관

Robot navigation under dynamic environment is considered as one of the key indications of machine’s intelligence. This paper proposed a program learning algorithm for robot navigation, so as to efficiently increase the intelligence of the machine. The Tolman mouse maze experiment was expanded to help the robot to develop intuitive intelligence, that it can lean the regularity the environment change. Firstly, the efficient environment map is constructed by SOM based on the cloud point generated randomly according to the environment. Then the robot will automatically choose how to reach the goal destination according to the shortest path generated by A star algorithm formerly. And corresponding reactions of the robot are determined by cycling time, which is the program we help the robot realize which path it is supposed to select. The validity of the proposed algorithm is proved by MATLAB and gazebo of ROS indigo, besides, we also did some physical experiments which have well shown the robots’ highly developed intelligence of finding the shortest path rapidly.