The Vision Guided Autonomous Mobile Robot

• Main Authors: Chin-Lang Huang, 黃錦郎
• Other Authors: Chin-Wen Chuang
• Format: Others
• Language: en_US
• Published: 2008
• Online Access: http://ndltd.ncl.edu.tw/handle/77678399846498970814

博士 === 義守大學 === 電機工程學系博士班 === 96 === In the modern life, it has gradually broken away from the work of too heavy and labor intensive, many labor intensive works are gradually replaced by the machinery and software. The most common examples are Mechanical arm, unmanned carrier, hoist tool, orienting the platform etc. The automatic mobile robots are also broadly used in industrial application, such as unmanned carriers in warehouse. With the great progress in the intelligent transportation systems, the unmanned automatic vehicles are often applied to drive automatically. The mechanical vision replaces the human’s eyes to be the feedback component. By the image processing, the necessary information can be figured out. However, due to the complicated calculation of image process, it will take a long calculation time from fetching image to making image information. Hence, a novel control rule that, namely the Grey-Fuzzy-Fuzzy controller, is proposed in this dissertation for vision guided control of unmanned automatic vehicles. The novel rule consists of the base-layer and upper-layer fuzzy controllers. The base-layer fuzzy controller is the classical fuzzy controller using the position error and the error difference to be the input variables. The Grey prediction is used to estimate the position error at the time of getting image information. Then, the upper-layer fuzzy controller uses the two input variables, which are the estimated position error and the estimated error difference, to correct the base-layer fuzzy controller’s output signal. Finally, an experimental unmanned automatic vehicle is developed to examine the potential of the proposed control scheme. The vision-based experiment of automatic driving of lane-following is carried out in this dissertation. The experimental results show the proposed controller will eliminate the swinging phenomenon and increase the accuracy while tracking. The experimental results also show the practical capability of the Grey-Fuzzy-Fuzzy controller.