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论文类型：期刊论文

发表时间：2008-02-01

发表刊物：Zidonghua Xuebao/Acta Automatica Sinica

收录刊物：EI、PKU、ISTIC

卷号：34

期号：2

页面范围：159-166

ISSN号：02544156

摘要：An on-the-fly, self-localization system is developed for mobile robot which is operative in a 3D environment with elaborative 3D landmarks. The robot estimates its pose recursively through a MAP estimator that incorporates the information collected from odometry and unidirectional camera. We build the nonlinear models for these two sensors and maintain that the uncertainty manipulation of robot motion and inaccurate sensor measurements should be embedded and tracked throughout our system. We describe the uncertainty framework in a probabilistic geometry viewpoint and use unscented transform to propagate the uncertainty, which undergoes the given nonlinear functions. Considering the processing power of our robot, image features are extracted in the vicinity of corresponding projected features. In addition, data associations are evaluated by statistical distance. Finally, a series of systematic experiments are conducted to prove the reliable and accurate performance of our system.