NDLI: Corrective Gradient Refinement for mobile robot localization

Content Provider	IEEE Xplore Digital Library
Author	Biswas, J. Coltin, B. Veloso, M.
Copyright Year	2011
Description	Author affiliation: Computer Science Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA (Veloso, M.) \|\| The Robotics Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA (Biswas, J.; Coltin, B.)
Abstract	Particle filters for mobile robot localization must balance computational requirements and accuracy of localization. Increasing the number of particles in a particle filter improves accuracy, but also increases the computational requirements. Hence, we investigate a different paradigm to better utilize particles than to increase their numbers. To this end, we introduce the Corrective Gradient Refinement (CGR) algorithm that uses the state space gradients of the observation model to improve accuracy while maintaining low computational requirements. We develop an observation model for mobile robot localization using point cloud sensors (LIDAR and depth cameras) with vector maps. This observation model is then used to analytically compute the state space gradients necessary for CGR. We show experimentally that the resulting complete localization algorithm is more accurate than the Sampling/Importance Resampling Monte Carlo Localization algorithm, while requiring fewer particles.
Starting Page	73
Ending Page	78
File Size	1190472
Page Count	6
File Format	PDF
ISBN	9781612844541
ISSN	21530858
e-ISBN	9781612844565
DOI	10.1109/IROS.2011.6094625
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-09-25
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computational modeling Proposals Sensors Robots Accuracy Vectors Three dimensional displays
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Computer Science Applications Computer Vision and Pattern Recognition Software

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