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Forest road surface detection using LiDAR-SLAM and U-Net

Hiroyuki Nakagomi, Yoshihiro Fuse, Yasuki Nagata, Hidehiko Hosaka, Hironaga Miyamoto, Masashi Yokozuka, Akiya Kamimura, Hiromi Watanabe, Tsutomu Tanzawa, Shinji Kotani

发表年份
2021
引用次数
5

摘要

Autonomous road surface following on forest roads by mobile robots and forestry vehicles carrying large logs is required for work in the forestry industry. In such situations, the detection of a passable road surface has to respond to changes in road geometry, surface conditions, and lighting. In this paper, we propose an efficient road detection method using LiDAR-SLAM and U-Net architectures: LiDAR-SLAM can accurately estimate the shape of the road in response to environmental changes, while U-Net architectures can efficiently estimate the edge of the road in a forest road. In the experiment, we used IoU (Intersection over Union) to evaluate the accuracy of the road surface detection in passing through a forest road. As a result, the proposed method achieved an IoU value of more than 90.2%.

关键词

LidarIntersection (aeronautics)Forest roadRoad surfaceRemote sensingComputer scienceMobile robotNet (polyhedron)Environmental scienceArtificial intelligence

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