Laser & Optoelectronics Progress, Volume. 61, Issue 8, 0812006(2024)
Small-Scale Rockfall Detection Method Based on Solid-State Lidar for Unstructured Transportation Roads in Open-Pit Mines
To address the challenges faced in the real-time detection of small-size rockfalls in open-pit mines during the transportation of ores using unmanned carts owing to suboptimal road conditions, intense lighting, and heavy dust, this study proposes a method for detecting small-size rockfalls in open-pit mines based on solid-state lidar. The proposed method employed a double-echo lidar for data acquisition, effectively reducing dust interference and extracting the driving area in front of the vehicle. Subsequently, a ground segmentation algorithm (straight-line fitting) based on fan surfaces was employed to segment the rough and unstructured terrains having slopes. Moreover, a hierarchical grid tree model known as octree was introduced to enhance the efficiency of neighborhood search. Furthermore, the two-color nearest pair method was applied to construct a graph, rapidly generating the clusters. Finally, the concept of adaptive clustering radius ε was adopted for clustering and obtaining the box models of small-size rockfalls. The experimental results demonstrate that the proposed method outperforms the k-d tree-accelerated DBSCAN algorithm, increasing the positive detection rate by 9.61 percentage points and reducing the detection time by 379.77 ms.
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Qinghua Gu, Jiawei Li, Lu Chen, Hejie Zhu. Small-Scale Rockfall Detection Method Based on Solid-State Lidar for Unstructured Transportation Roads in Open-Pit Mines[J]. Laser & Optoelectronics Progress, 2024, 61(8): 0812006
Category: Instrumentation, Measurement and Metrology
Received: Mar. 2, 2023
Accepted: Apr. 12, 2023
Published Online: Apr. 16, 2024
The Author Email: Li Jiawei (1205854732@qq.com)