3D grid and particle based SLAM for a humanoid robot
3D grid and particle based SLAM for a humanoid robot
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DOI：
10.1109/ichr.2009.5379602
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发表时间：
2009-12
期刊：
影响因子：
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通讯作者：
Nosan Kwak;O. Stasse;T. Foissotte;K. Yokoi
中科院分区：
文献类型：
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作者：
Nosan Kwak;O. Stasse;T. Foissotte;K. Yokoi
最近，对于日常使用，出现了通过人形机器人识别像家庭环境一样的世界的必要性。立体视觉作为一种观察传感器，是仿人机器人获取环境数据最常用的设备，但它比激光传感器更容易出错。为了克服立体视觉的不准确性，我们提出了一种基于粒子的SLAM技术，使SLAM后验估计的多个假设。基于粒子的三维栅格地图SLAM的主要困难是计算成本高。为了减少计算成本，我们还提出了一个调度方法的时间时，匹配和粒子参与匹配过程。通过与类人机器人HRP-2的实验，它表明，所提出的方法可以降低计算成本，同时保持估计精度。
Necessity to recognize the world like a home environment by a humanoid robot has recently been arisen for daily usages. As an observation sensor, stereo vision is the most common device for a humanoid robot to obtain the environmental data, but it is more erroneous than a laser sensor. To overcome the inaccuracy of stereo vision, we propose a particle-based SLAM technique so that the SLAM posterior is estimated by multiple hypotheses. The major difficulty of the particle-based SLAM with 3D grid maps is the high computational cost. To reduce the computational cost, we also propose a scheduling method for the time when to match and for particles that engage in the matching process. Through experiments with a humanoid robot, HRP-2, it is shown that the proposed approach can reduce the computational cost while preserving estimation accuracy.