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	ENVIRONMENTAL PERCEPTION FOR HUMANOIDS USING GAUSSIAN PROCESS REGRESSION
	Luo, Dingsheng ; Ding, Yaoxiang ; Liu, Zhan ; Wu, Xihong
	2016
关键词	Environmental Perception Intelligent Behavior Humanoid Robots Gaussian Process Regression PUSH RECOVERY
英文摘要	As humanoids are expected acting in the real world to humanly and intelligently complete some high-level tasks, precisely perceiving the changes of environments is thus an essential premise. Due to the complexity of real-world environments, how to exactly perceive the environmental changes with limited sensors equipped on the robot becomes a challenging problem. Though this problem can be solved by establishing direct sensory mappings or employing probabilistic filtering methods, the nonlinearity and uncertainty caused by the high degree-of-freedom of the robots and the complexity of the environment result in tough modeling difficulties. In this paper, an alternative learning approach for addressing such modeling problems under the Gaussian process regression framework is proposed. The evaluations under perceptual tasks for two representative environmental changes, i.e. unknown pushing and sloped terrains, reveal the potential of the proposed approach in coping with the nonlinearity and uncertainty of environmental perception for humanoids.; CPCI-S(ISTP); dsluo@cis.pku.edu.cn; yxding@cis.pku.edu.cn; Liuz@cis.pku.edu.cn; wxh@cis.pku.edu.cn; 345-354
语种	英语
出处	18th Climbing and Walking Robots Conference (CLAWAR)
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/459782]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Luo, Dingsheng,Ding, Yaoxiang,Liu, Zhan,et al. ENVIRONMENTAL PERCEPTION FOR HUMANOIDS USING GAUSSIAN PROCESS REGRESSION. 2016-01-01.

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