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Publication Details

Reference TypeConference Paper
Author(s)M. Wüthrich, P. Pastor, L. Righetti, A. Billard and S. Schaal
TitleProbabilistic depth image registration incorporating nonvisual information
Journal/Conference/Book TitleRobotics and Automation (ICRA), 2012 IEEE International Conference on
AbstractIn this paper, we derive a probabilistic registration algorithm for object modeling and tracking. In many robotics applications, such as manipulation tasks, nonvisual information about the movement of the object is available, which we will combine with the visual information. Furthermore we do not only consider observations of the object, but we also take space into account which has been observed to not be part of the object. Furthermore we are computing a posterior distribution over the relative alignment and not a point estimate as typically done in for example Iterative Closest Point (ICP). To our knowledge no existing algorithm meets these three conditions and we thus derive a novel registration algorithm in a Bayesian framework. Experimental results suggest that the proposed methods perform favorably in comparison to PCL [1] implementations of feature mapping and ICP, especially if nonvisual information is available. View full abstract
Short TitleProbabilistic depth image registration incorporating nonvisual information
Custom 3papers2://publication/uuid/06FEBB85-CEC3-4F22-92A9-3E5C29179F7E
Accession Number6225179
Electronic Resource Number10.1109/ICRA.2012.6225179
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