Performance Comparison of Visual Odometry and Filter-based Localization
碩士 === 淡江大學 === 機械與機電工程學系碩士班 === 102 === This study investigates the performance of two robot localization algorithms based on filter method and visual odometry (VO), respectively. A handhold binocular vision system is used as the sensing device which is free-moving in the environment. The filter-ba...
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| Format: | Others |
| Language: | zh-TW |
| Published: |
2014
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| Online Access: | http://ndltd.ncl.edu.tw/handle/71702036373464846349 |
| Summary: | 碩士 === 淡江大學 === 機械與機電工程學系碩士班 === 102 === This study investigates the performance of two robot localization algorithms based on filter method and visual odometry (VO), respectively. A handhold binocular vision system is used as the sensing device which is free-moving in the environment. The filter-based localization algorithm uses the extended Kalman filter to simultaneously implement the tasks of localization and mapping, and then utilizes the localization function. The VO-based localization algorithm uses random sample consensus (RANSAC) to solve the location determination problem. This study investigates the issues include: calibration and measurement of binocular vision system, implementation of filter-based and visual odometer based robot localization algorithms, discussion of the advantages and disadvantages of these two localization algorithms using in an unknown environment.
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