Moving Object Detection and Tracking Using Binocular Vision Based on Spatial Constraints of Static Environment
碩士 === 淡江大學 === 機械與機電工程學系碩士班 === 99 === This thesis presents a visual simultaneous localization, mapping and moving object tracking (SLAMMOT) based on extended Kalman filter (EKF). First, we use the geometric constraints of static landmarks in three-dimensional space to design the algorithms of data...
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| Format: | Others |
| Language: | zh-TW |
| Published: |
2011
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| Online Access: | http://ndltd.ncl.edu.tw/handle/60285200837621829570 |
| Summary: | 碩士 === 淡江大學 === 機械與機電工程學系碩士班 === 99 === This thesis presents a visual simultaneous localization, mapping and moving object tracking (SLAMMOT) based on extended Kalman filter (EKF). First, we use the geometric constraints of static landmarks in three-dimensional space to design the algorithms of data association and map management. Since these algorithms are independent of the EKF estimator, the SLAMMOT system can recover from the problem of robot kidnapped automatically. Second, we use the same geometric constraints to develop the algorithm for moving object detection. The developed algorithms are integrated with the EKF estimator to carry out the experiments of SLAMMOT tasks in indoor environments.
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