煤炭工程 ›› 2016, Vol. 48 ›› Issue (3): 113-115.doi: 10.11799/ce201603035

• 研究探讨 • 上一篇    下一篇

基于改进粒子滤波的煤矿机器人定位方法研究

张鹏   

  1. 中煤科工集团西安研究院物研中心
  • 收稿日期:2015-10-21 修回日期:2015-12-07 出版日期:2016-03-10 发布日期:2016-04-08
  • 通讯作者: 张鹏 E-mail:13152090398@163.com

Study on localization Method for Coal Mining Robot Based on Improved Particle Filter Algorithm

  • Received:2015-10-21 Revised:2015-12-07 Online:2016-03-10 Published:2016-04-08

摘要: 针对基本粒子滤波方法在煤矿机器人井下未知空间定位应用中存在的粒子退化问题,提出了一种基于马尔可夫链蒙特卡尔重采样理论的改进粒子滤波定位方法,以增强粒子滤波的稳定性,并应用该方法与传统的扩展卡尔曼滤波定位方法进行了机器人在未知狭小空间中的定位仿真实验对比研究。实验结果表明,该方法比扩展卡尔曼滤波定位方法有更高的精度和实时性,有效解决了煤矿井下未知空间机器人预测定位问题。

关键词: 改进粒子滤波, 定位, 未知空间, 煤矿井下, 机器人

Abstract: To solve the basic particle filter in the unknown space localization method of particle degradation problems, an improved particle filter algorithm based on MCMC was proposed. This particle filter robustness was enhanced. The localization simulation test using improved particle filter was developed which was applied in coal mining robot in unknown underground space. The simulation test results showed that the localization using improved particle filter had more locating accuracy in unknown underground space and better computational real-time ability than extended Kalman filter. This method has solved the pre-localization problem of coal mining robot underground.

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