LiDAR-Based Negative Obstacle Detection for Unmanned Ground Vehicles in Orchards
Peng Xie, Hongcheng Wang, Yexian Huang, Qiang Gao, Zihao Bai, Linan Zhang, Yunxiang Ye · 2024
Read LiDAR-Based Negative Obstacle Detection for Unmanned Ground Vehicles in Orchards by Peng Xie, Hongcheng Wang, Yexian Huang, Qiang Gao, Zihao Bai, Linan Zhang, Yunxiang Ye (2024) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-11679008.txt.
Description
Peng Xie and co-authors detect ditches and potholes for orchard robots with tilted LiDAR in this 2024 paper. Holes are negative obstacles that ground vehicles cannot see with level sensors. Tilting the scanner down at forty degrees shrank its blind zone from three meters to a fifth of a meter. Ground point density rose tenfold as well.
Detection rules read height, density, and spacing jumps across the point cloud. Merging several frames steadies the calls. Field trials hit a 92.7 percent success rate. The farthest reliable detection reached about eight meters. Orchard automation stalls on simple ground hazards more than on fancy perception. A cheap mounting change plus geometry rules solves most of it here.
Catalog record
| CREATOR | Peng Xie, Hongcheng Wang, Yexian Huang, Qiang Gao, Zihao Bai, Linan Zhang, Yunxiang Ye |
|---|---|
| YEAR | 2024 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 47 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |