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- Title
基于激光和视觉传感器融合的定位与建图.
- Authors
赵以恒; 周志峰
- Abstract
Location and mapping is one of the key technologies for autonomous driving. With limitations of lidar sensors or vision sensors, the advantages of diflferent sensors can be brought into play through multisensor fusion and the accuracy and robustness of location and mapping can be improved. The Harris algorithm was optimized for comer extraction, the key frame was used to optimize the feature point matching algorithm, and then the nonlinear least square method was used for back-end optimization. The location and mapping experiments were carried out on the test platform to verify the algorithm, and the positioning error was analyzed with the EVO tool. The result shows that the error of the proposed back-end optimization algorithm is 13% less than that of a single sensor.
- Subjects
OPTIMIZATION algorithms; IMAGE sensors; LEAST squares; AUTONOMOUS vehicles; MULTISENSOR data fusion; DRIVERLESS cars
- Publication
Journal of Shanghai University of Engineering Science / Shanghai Gongcheng Jishu Daxue Xuebao, 2022, Vol 36, Issue 4, p392
- ISSN
1009-444X
- Publication type
Article