A Vision-Based Dead-Reckoning Vehicle Navigation System

• Main Authors: Tsai-Yu Chia, 蔡毓佳
• Other Authors: W. W. Kao
• Format: Others
• Language: zh-TW
• Published: 2007
• Online Access: http://ndltd.ncl.edu.tw/handle/w8ebw8

碩士 === 國立臺灣科技大學 === 機械工程系 === 95 === A vision-based dead-reckoning method was developed for vehicle navigation in tunnel environments. Traditionally, dead-reckoning method is implemented by distance and heading sensors and error accumulations become inevitable with sensor biases and noises. Using differences of consecutive images, displacement vectors between images can be derived. And dead-reckoning can be achieved. The randomness characteristics of the vision derived displacement errors result in less severe error accumulation in the dead-reckoning operation. The algorithm utilizes the lightings in tunnels as feature points. These lights are used to derive curves described by polynomials and the relative displacements of lights in different images are used to calculate the vehicle displacements between images. The experimental results show very good accuracy in the longitudinal displacement calculation but there are still rooms for the angular displacement accuracy improvement. Nevertheless, acceptable dead-reckoning results can be obtained by processing sequential images within the tunnel without the need of any traditional dead-reckoning sensors, and this method opens new possibilities of vehicle navigation in tunnel situations purely based on vision-processing.