PERCEPTION
Incremental probabilistic geometry estimation for robot scene understanding
Louis-Kenzo Cahier, Tetsuya Ogata, Hiroshi G. Okuno
- Year
- 2012
- Citations
- 2
Abstract
Our goal is to give mobile robots a rich representation of their environment as fast as possible. Current mapping methods such as SLAM are often sparse, and scene reconstruction methods using tilting laser scanners are relatively slow. In this paper, we outline a new method for iterative construction of a geometric mesh using streaming time-of-flight range data. Our results show that our algorithm can produce a stable representation after 6 frames, with higher accuracy than raw time-of-flight data.
Keywords
Computer visionComputer scienceProbabilistic logicMobile robotRepresentation (politics)Artificial intelligenceRange (aeronautics)Simultaneous localization and mappingRobotIterative method
Related papers
OTHER
📊 26,957 cites
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
PERCEPTION
📊 22,245 cites
Artificial intelligence: a modern approach
1995
OTHER
📊 18,993 cites
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
SWARM
📊 14,853 cites
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002