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Article overview
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Gaussian Process Autonomous Mapping and Exploration for Range Sensing Mobile Robots | | Maani Ghaffari Jadidi
; Jaime Valls Miro
; Gamini Dissanayake
; | | Date: |
2 May 2016 | | Abstract: | A framework for incremental autonomous mapping and exploration of unknown
environments using the recently emerged Gaussian Process (GP) continuous
occupancy mapping techniques is proposed in this article. The technique is able
to exploit structural dependencies present in the environment as well as handle
sparse sensor measurements. A strategy based on mutual information surfaces
between the current map of the environment and predicted sensor readings using
a one-step look ahead and macro-action concept is used to generate the control
actions. We present results using the publicly available Intel Research Lab
dataset with maps generated with occupancy grid-based nearest frontier,
GP-based nearest frontier, and the proposed GP and mutual information-based
exploration techniques. Maps are compared using the receiver operating
characteristic curve and the area under the curve to demonstrate the accuracy
of the proposed incremental mapping technique. Statistical significance test
using two-sample t-test demonstrates the effectiveness of the proposed
technique in terms of map entropy reduction rate and produced map quality ($p
leq 0.05$). | | Source: | arXiv, 1605.0335 | | Services: | Forum | Review | PDF | Favorites | |
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