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摘要: 摘要利用基于自适应粒子滤波与地图匹配方法实现了机器人的自定位. 提出了一种采用距离相似性度量以及几何相似性度量的二次更新方法,对常规的基于激光测距仪的粒子滤波定位方法进行了改进,既增强了系统的鲁棒性,又提高了系统的计算效率. 仿真结果表明,移动机器人利用该定位方法可以在室内环境中利用自然特征进行鲁棒高效的自定位.Abstract: Robot self-localization is realized by using adaptive particle filter scheme with map-matching algorithm. A two-phase-updating method based on similarity measurements of range and geometry is proposed to improve the performance of general particle filter localization which uses a laser range finder. The algorithm not only enhances the robustness of the system, but also increases the computational effciency. Simulation results demonstrate that by using the proposed algorithm and nature characteristics in indoor environment, mobile robot can localize itself accurately androbustly.
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Key words:
- Adaptive particle filter /
- map-matching /
- laser range finder /
- self-localization
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