摘要
针对机器人采用视觉传感器和激光测距传感器单独定位的缺陷,提出一种融合视觉传感器和激光测距传感器感知信息的移动机器人Monte Carlo自定位方法。视觉目标识别过程中,只采用激光测距信息单独进行粒子集更新;当视觉目标识别完成,利用码盘信息对视觉定位信息进行修正,然后融合激光测距信息进行粒子集的同步更新。视觉信息的全局性和激光测距的快速性得到互补。实验表明,运用异质传感器信息融合明显地加快了粒子集的收敛,提高了移动机器人的自定位精度。
To deal with the localization disadvantage of robot only equipped with monocular camera or LRF（laser range finder sensor）,a novel Monte Carlo method based on monocular camera and LRF sensor information fusion is proposed.During the vision object recognition,particle sets is updated by LRF sensor information;and the vision object recognition completed,the vision sensor information modified by the encoders is fused with that from LRF sensor information to synchronously update particle sets.Both monocular camera and LRF advantage is fully utilized.The simulation results show that particle sets is converged faster than those from either range-based or vision-based localization,and the self-localization precision is obviously improved by the heterogeneous sensor information fusion.
出处
《电子测量与仪器学报》
CSCD
2011年第1期38-43,共6页
Journal of Electronic Measurement and Instrumentation
基金
湖南省自然科学-湘潭联合研究基金(编号:09JJ8006)资助项目
