Localisation for Autonomous Humanoid Navigation
Localisation for Autonomous Humanoid Navigation
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DOI：
10.1109/ichr.2006.321357
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发表时间：
2006-12
期刊：
影响因子：
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通讯作者：
S. Thompson;S. Kagami;K. Nishiwaki
中科院分区：
文献类型：
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作者：
S. Thompson;S. Kagami;K. Nishiwaki
由于难以实现稳定的双足运动，复杂环境中的自主人形导航需要高精度。特别是，需要准确的定位估计来规划狭窄楼梯上的足迹放置。本文报告了一种基于精确 6DOF 粒子滤波器的定位系统的开发，用于在已知 2.5 维地图内移动的人形机器人。安装在机器人头部的激光测距传感器可对环境进行 120 度平面扫描，最远距离可达 4 米。通过仔细表征机器人的里程计模型、引入用于粒子预测的新颖运动模型以及解耦人形位置不确定性的有界和无界分量来实现定位精度。这种新颖的运动通过对人形机器人的运动进行建模并包括采样时间和位置精度的不确定性来预测更准确的粒子分布。此外，报告的系统估计定位不确定性分布并实现基于模型的注视吸引行为以进一步减少定位误差。
Autonomous humanoid navigation in non-trivial environments requires high precision accuracy due to the difficulty in achieving stable bipedal locomotion. In particular, an accurate localisation estimate is needed to plan footstep placement on a narrow staircase. This paper reports the development of an accurate 6DOF particle filter based localisation system for a humanoid robot moving within a known 2.5 dimensional map. A laser range sensor mounted within the robot's head makes 120 degree planar scans of the environment up to a distance of 4 meters. Localisation accuracy is achieved by carefully characterising the robot's odometry model, introducing a novel motion model for particle prediction and decoupling the bounded and unbounded components of humanoid position uncertainty. The novel motion predicts a more accurate particle distribution by modeling the motion of a humanoid robot and including uncertainty in sampling time as well as position accuracy. In addition the reported system estimates the localisation uncertainty distribution and implements a model based gaze attraction behaviour to further reduce localisation error.