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- Title
采用静态数据增强的AGV定位与姿态修正研究.
- Authors
翁润庭; 张春良; 岳夏; 李子涵; 龙尚斌; 郑仲之
- Abstract
Automated guided vehicle (AGV) equipped with laser radar are widely used in the transportation of workpieces in intelligent factories. However, due to the influence of obstacles and moving objects, AGV has a weak ability to distinguish the position and posture in the workshop. In order to solve the problem of positioning and posture recognition, a new point cloud data fusion position and posture recognition strategy was proposed, using the high-precision static total station data to fuse the local and low-precision data of the laser radar, and the vector weight matching method was proposed to complete the indoor positioning of the AGV.A sampling grid convolution method was designed to realize the rapid preliminary location of heterogeneous data; the reference area for adaptive search of total station data was established and mapped to the corresponding area of laser radar data; finally, the pose parameters of AVG were obtained by vector weight matching. The above method was tested in 6 m×8 m indoor space. The results show that the positioning accuracy of ±7 mm and the posture control recognition accuracy of ±1.4° can be achieved, and the scanning error of laser radar can be accurately compensated, and the position and posture recognition ability of AGV can be improved.
- Publication
Machine Tool & Hydraulics, 2024, Vol 52, Issue 9, p1
- ISSN
1001-3881
- Publication type
Article
- DOI
10.3969/j.issn.1001-3881.2024.09.001