巷道掘进机多传感融合定位系统及试验研究
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刘送永,男,1981年11月生,教授。主要研究方向为煤矿采掘装备智能化、煤矿特种机器人。曾发表《Path planning for robotic manipulator in complex multi-obstacle environment based on improved-RRT》(《IEEE/ASME Transactions on Mechatronics》2022,Vol.27,No.6)等论文。 E-mail:lsycumt@163.com

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TH89;TP271.4

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江苏省杰出青年基金资助项目(BK20211531);江苏省高等学校基础科学(自然科学)研究资助项目(22KJB440004);徐州市重点研发计划资助项目(KC22404);国家自然科学基金面上资助项目(51975573);江苏师范大学博士学位教师科研支持资助项目(22XFRS011)


Multi‑sensor Fusion Positioning System and Experimental Study of Roadheader
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    摘要:

    煤矿巷道掘进机的自主精确定位是煤矿掘进智能化发展的基础,而复杂的掘进工艺和恶劣的掘进环境使得掘进机定位存在自主性不足、精度低以及易受环境干扰等问题。为实现巷道掘进机自主精确定位,首先,基于扩展卡尔曼滤波构建了里程计辅助惯性定位系统以约束惯性定位的误差发散;其次,结合掘进机施工工艺提出柔性零速校正方法,进一步提升掘进机惯性定位精度;然后,基于误差状态卡尔曼滤波和多状态约束模型实现了惯性、视觉和里程定位的高效融合;最后,搭建了掘进机在暗环境下自主定位的样机试验系统。实验结果表明:所提柔性零速校正方法可以提升掘进机定位精度约21.64%;所提掘进机多传感融合定位系统三轴定位误差分别可达到横向0.13 m以内、前向0.17 m以内、天向0.02 m以内,相比独立惯性和视觉系统的定位精度分别提升49.62%和57.71%。实验结果验证了所提方法与系统的可行性与有效性,满足煤矿规程中巷道掘进机定位需求。

    Abstract:

    The autonomous and accurate positioning of roadheader is the foundation of intelligent development of coal mine roadway excavation. However, the complicated tunneling technology and harsh tunneling environment make the positioning of roadheader faces problems such as insufficient autonomy, low accuracy and poor immunity to disturbance. In order to realize the autonomous and accurate positioning of roadheader, an odometer-aided inertial positioning system is constructed based on extended Kalman filter to restrain the error divergence of pure inertial positioning. Combined with the construction technology of roadheader, a flexible zero velocity updating method is proposed to further improve the inertial positioning accuracy of roadheader. The efficient integration of inertia, vision and mileage positioning is realized based on error state Kalman filter and multi-state constraint model. A prototype test system of roadheader in dark environment is also built. The experimental results show that the proposed flexible zero velocity updating method can improve the pure inertial positioning accuracy by 21.64%. The three-axis positioning errors of the proposed multi-sensor fusion positioning system of roadheader are within 0.13 meters of lateral positioning error, 0.17 meters of forward positioning error and 0.02 meters of upwards positioning error, which improves by 49.62% and 57.71% compared with the independent inertial and visual systems, respectively. The experimental results verify the feasibility and effectiveness of the proposed method and system, and the positioning accuracy of the proposed system meets the requirements of roadway excavation in coal mine.

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  • 收稿日期:2022-05-09
  • 最后修改日期:2022-08-10
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  • 在线发布日期: 2023-06-29
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