CHEN Xianzhong, LIU Rongjie, ZHANG Sen, ZENG Hui, YANG Xinpeng, DENG Hao. Development of millimeter wave radar imaging and SLAM in underground coal mine environment[J]. Journal of China Coal Society, 2020, 45(6). DOI: 10.13225/j.cnki.jccs.ZN20.0316
Citation: CHEN Xianzhong, LIU Rongjie, ZHANG Sen, ZENG Hui, YANG Xinpeng, DENG Hao. Development of millimeter wave radar imaging and SLAM in underground coal mine environment[J]. Journal of China Coal Society, 2020, 45(6). DOI: 10.13225/j.cnki.jccs.ZN20.0316

Development of millimeter wave radar imaging and SLAM in underground coal mine environment

  • Environmental detection and underground space navigation is an important research direction in the field of intelligent information for coal mines,which is very important for the realization of unmanned,fully automatic and intel- ligent coal mine production. With the development of the Fifth Generation Mobile Networks (5G) and mmWave ima- ging technology,the integration of hardware and software design of millimeter wave in the detection and communication has been a considerable growth. The 5G communication technology relies on the characteristics of high speed,low de- lay and high bandwidth,which brings great changes to the existing radio communication technology. Compared with laser,mmWave radar has the characteristics of low cost,anti-jamming,and the point cloud pixels for each frame of image are 1-2 orders less than that of laser,which makes its more popular in the 3D imaging of underground environment and simultaneous localization and mapping (SLAM). The V2X (Vehicle to Everything) technology based on 5G com- munication combined with millimeter wave SLAM navigation provides a new solution for the autonomous navigation of coal mine robots. This paper systematically reviews the problems faced by the autonomous navigation of coal mine ro- bots and the realization of intelligent coal mine,and the research progress of mmWave imaging recently. The sparse feature extraction method for high-resolution imaging,and also the schematic diagram of communication and signal ac- quisition for multiple module groups are introduced. The processing strategy and algorithm evaluation of sparse point cloud and the research status and development direction of deep learning in sparse point cloud processing of mmWave imaging are summarized. Finally,the problems and challenges of SLAM map construction,path planning and obstacle avoidance in the underground mining environment,the research status of SLAM algorithm applied to different environ- ments and SLAM navigation algorithm are categorized and elaborated. In addition,the problems that need to be solved in the further study of millimeter wave communication and navigation and possible future development directions are proposed.
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