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金属矿山 ›› 2023, Vol. 52 ›› Issue (11): 221-227.

• 机电与自动化 • 上一篇    下一篇

融合场景理解与机器视觉的矿山巡检机器人导航避障研究

王 斌1,2 田宝雄1 赵明辉3,4
  

  1. 1. 国能神东煤炭集团有限责任公司,内蒙古 鄂尔多斯 017200;2. 中国神华能源股份有限公司神东煤炭分公司,陕西 神木 719315;3. 同济大学电子与信息工程学院,上海 201804;4. 中煤科工集团上海有限公司,上海 200030
  • 出版日期:2023-11-15 发布日期:2024-01-02
  • 基金资助:
    中国神华能源股份有限公司神东煤炭分公司科技创新项目(编号:E210100270);上海市科委项目(编号:15111105500)。

Study on Mine Inspection Robot Navigation Obstacle Avoidance Combining Scene Understanding and Machine Vision

WANG Bin1,2 TIAN Baoxiong1 ZHAO Minghui3,4 #br#   

  1. 1. Guoneng Shendong Coal Group Co. ,Ltd. ,Ordos 017200,China;2. Shendong Coal Branch,China Shenhua Energy Company Limited,Shenmu 719315,China;3. College of Electronics and Information Engineering,Tongji University,Shanghai 201804,China;4. China Coal Science and Technology Group Shanghai Co. ,Ltd. ,Shanghai 200030,China
  • Online:2023-11-15 Published:2024-01-02

摘要: 近年来,随着机器人技术和人工智能技术的迅猛发展,越来越多的矿山企业开始采用机器人进行巡检 和监测,以提高生产效率和降低人工巡检成本。 然而,由于矿山环境复杂多变,存在大量的障碍物和危险因素,传统的 巡检机器人往往不能满足实际需求,需要引入一些先进的场景理解和机器视觉技术,以提高机器人的导航和避障能 力。 提出了一种基于融合场景理解与机器视觉的矿山巡检机器人导航避障方法。 首先,通过机器视觉技术对矿山环 境进行识别和定位,获取当前机器人所处的位置和周围场景信息。 然后,利用场景理解技术对矿山场景进行分析,包 括识别各种矿石、设备和人员,并对矿山环境中的障碍物进行检测和分类。 最后,将融合后的场景理解和机器视觉信 息应用于机器人的导航和避障控制。 试验结果表明:所提方法能够有效提高机器人在复杂矿山环境下的导航和避障 能力,对于推动智能矿山建设、提高矿山生产效率、降低巡检成本具有一定的意义。

关键词: 矿山巡检机器人, 智能矿山, 场景理解, 机器视觉, 导航避障

Abstract: In recent years,with the rapid development of robot technology and artificial intelligence technology,more and more mining enterprises begin to use robots for inspection and monitoring,in order to improve production efficiency and reduce the cost of manual inspection. However,due to the complex and changeable mine environment,there are a large number of obstacles and dangerous factors,traditional inspection robots often cannot meet the actual demand,it is necessary to introduce some advanced scene understanding and machine vision technology,in order to improve the robot′s navigation and obstacle avoidance ability. In this paper,a navigational obstacle avoidance method of mine inspection robot based on integrated scene understanding and machine vision is studied. First of all,the mine environment is identified and positioned by machine vision technology to obtain the position and surrounding scene information of the current robot. Then,the scene understanding technology is used to analyze the mine scene,including identifying various ores,equipment and personnel,and detecting and classifying obstacles in the mine environment. Finally,the integrated scene understanding and machine vision information are applied to the navigation and obstacle avoidance control of the robot. The experimental results show that the proposed method can effectively improve the robot′s navigation and obstacle avoidance ability in complex mine environment,have certain significance for promoting the construction of intelligent mine,improving mine production efficiency and reducing inspection cost.

Key words: mine inspection robot,intelligent mine,scene understanding,machine vision,navigational obstacle avoidance