基于AMC算法的变电站巡检机器人地图创建与定位
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TM764

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国家自然科学基金资助项目(51507058)


The global map′s creating and positioning of substation inspection robot based on adaptive Monte Carlo particle filter algorithm
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    摘要:

    变电站的设备巡检工作对于保证供电可靠性起着至关重要的作用,传统的人工巡检方式效率低,工作量大,难以取得理想的结果。机器人巡检已成为智能电网未来发展的趋势。文中研究变电站巡检机器人实时定位和地图创建(SLAM),根据巡检业务特征实现SLAM建模,提出一种基于自适应蒙特卡洛(AMC)算法的巡检机器人SLAM方法,考虑变电站实际环境动态和巡检机器人特征的复杂性,实现机器人二维地图的创建和实时定位。仿真结果表明,基于AMC的巡检机器人SLAM定位精度更高,针对不同过程噪声的抗干扰性更强,更适用于变电站巡检机器人的SLAM问题解决和实践应用。

    Abstract:

    Substation equipment inspection plays a vital role in the reliability of power supply. The traditional manual inspection method is inefficient and heavy workload, and it is difficult to achieve ideal results. Robot inspection has become the future trend of smart grid development. The real-time localization and map creation of substation inspection robot are studied. A SLAM method of inspection robot based on adaptive Monte Carlo algorithm is proposed. Considering the dynamic environment of substation and the complexity of inspection robot′s characteristics, the two-dimensional map creation and real-time localization of robot are realized. The simulation results show that the SLAM positioning accuracy of inspection robot based on AMC algorithm is higher, and the anti-jamming ability for different process noise is stronger. Therefore, it is more suitable for SLAM problem solving and practical application of substation inspection robot.

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谢林枫,蒋超,孙秋芹,王昊炜,宋庆武,官国飞.基于AMC算法的变电站巡检机器人地图创建与定位[J].电力工程技术,2019,38(5):16-23

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历史
  • 收稿日期:2019-03-20
  • 最后修改日期:2019-04-30
  • 录用日期:2019-07-02
  • 在线发布日期: 2019-09-30
  • 出版日期: 2019-09-28