Adaptive and A-star RRT Algorithm Applied in the Navigation and Control of an Unmanned Vehicle

• Main Authors: Kuan-Yin Wang, 王冠尹
• Other Authors: 王立昇
• Format: Others
• Language: zh-TW
• Published: 2017
• Online Access: http://ndltd.ncl.edu.tw/handle/98naa7

碩士 === 國立臺灣大學 === 機械工程學研究所 === 105 === The main purpose of this research is to improve the efficiency of RRT (Rapidly-exploring Random Tree) algorithm for path planning of an unmanned vehicle, which can be used in outdoor navigation control and obstacle avoidance. In recent years, RRT has been wildly used in path planning. Along with path-smoothing method, RRT can generate proper path for the motion of a vehicle. In order to reduce the operational time of RRT algorithm, the concepts of A*-algorithm was used to modify the RRT algorithm. In the A*-algorithm, the smaller the heuristic function is, the smaller the cost for reaching the end point is. Furthermore, an adaptive design for the different edge length is introduced to balance search efficiency and obstacle avoidance. An unmanned vehicle with GPS receiver, stereo camera and electronic compass was used to justify our algorithm. From the experimental results, the adjustment for RRT algorithm, which is termed AASRRT, is shown to be beneficial for effective and proper path planning to reach the destination with obstacles being avoided.