煤矿场景下基于RGBD的视觉导航技术
Visual navigation technology based on RGBD in coal mine scene
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摘要: 为解决煤矿机器人现有自主导航技术的局限性，提出了1种煤矿场景下基于RGBD的视觉导航技术。研究了视觉导航的总体架构，并对各个功能模块进行了设计描述；研究了地图创建方法，将ORB_SLAM2算法生成的连续帧间位姿进行关系变换，采用逐帧的RGBD点云拼接，获得了稠密的点云地图；设计了巡检机器人的自主定位和路径规划实现流程，结合蒙特卡洛、D*及DWA算法完成了机器人的精准定位与导航；建立了该视觉导航技术的测试平台，并利用该平台进行了系列化的模拟测试。测试结果表明：煤矿场景下基于RGBD的视觉导航技术能够满足煤矿井下轮式巡检机器人的自主行走功能需求，定位精度良好。Abstract: In order to solve the limitations of the existing autonomous navigation technology of coal mine robot, a visual navigation technology based on RGBD in coal mine scene is proposed. The overall architecture of visual navigation is studied, and each functional module is designed and described; the map creation method is studied, the pose relationship between consecutive frames generated by ORB_SLAM2 algorithm is transformed, and the dense point cloud map is obtained by frame RGBD point cloud splicing; the implementation process of autonomous positioning and path planning of inspection robot is designed. Combined with Monte Carlo, D* and DWA algorithms, the accurate positioning and navigation of robot are completed; the test platform of the visual navigation technology is established, and a series of simulation tests are carried out using the platform. The test results show that the visual navigation technology based on RGBD in the coal mine scene can meet the autonomous walking function requirements of the wheeled inspection robot in the coal mine, with good positioning accuracy.
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Keywords:
- coal mine robot /
- visual navigation /
- RGBD /
- map creation /
- autonomous positioning /
- path planning
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