对于集成ORB-SLAM3和深度视觉的智能地下采矿设备的可行性域建设和表征方法
Siya Sun1,2, Xiaotong Han1, Hongwei Ma2,3
1College of Electrical and Control Engineering, Xi'an University of Science and Technology, Xi'an 710054, China.
Sensors (Basel, Switzerland)
|February 13, 2026
概括
这项研究引入了一种新方法,用于使用RGB-D摄像头和ORB-SLAM3创建地下煤矿的3D数字地图. 该方法增强了环境感知,并为自主操作创建了高效,准确的3D可行的空间表示.
科学领域:
- 机器人和计算机视觉 机器人和计算机视觉
- 地理空间信息科学 地理空间信息科学
- 采矿工程 采矿工程 采矿工程
背景情况:
- 地下煤矿对环境的感知构成重大挑战,原因是灰尘,照明不良和狭窄的空间.
- 现有的方法在这些恶劣条件下,难以一致和高效地表示可行的工作空间域.
- 准确的3D空间理解对于自主导航,路径规划和采矿操作中的安全至关重要.
研究的目的:
- 为地下采矿环境开发一个强大的数字空间构造和表示方法.
- 克服环境感知和可行域名表示的局限性,这是由于具有挑战性的地下条件造成的.
- 为自主采矿应用提供可靠的3D数字空间基础.
主要方法:
- 整合RGB-D深度视觉与ORB-SLAM3进行增强的空间映射.
- 开发一个"密集-稀疏合作"OAK-DenseMapper Pro模块,用于高质量的点云重建.
- 将密集的点云转换为一个内存高效的概率八度占用地图,用于可扩展的3D表示.
主要成果:
- 使用ChArUco板实现了高精度的RGB-D摄像头校准,提高了几何参数的可靠性.
- 在密集映射点数 (约. 38%的增长),并减少了轨迹误差 (减少了高达10%的误差).
- 将地图内存足迹减少到原始点云的0.5%左右,具有高效的八树转换.
结论:
- 拟议的方法可以实现复杂的地下煤矿的实时,高效和一致的3D可行域表示.
- 数字空间基础支持关键应用程序,如路径规划和安全避开障碍.
- 这种方法提高了在具有挑战性的地下环境中自主运行的可靠性和效率.
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