6533b828fe1ef96bd1287b6b
RESEARCH PRODUCT
Automatic place detection and localization in autonomous robotics
Irene MacalusoAntonio ChellaLorenzo Rianosubject
Computer sciencebusiness.industryFeature extractionRoboticsComputer Science Applications1707 Computer Vision and Pattern RecognitionMixture modelMachine learningcomputer.software_genreObject detectionsymbols.namesakeControl and Systems EngineeringsymbolsRobotUnsupervised learningArtificial intelligenceHidden Markov modelbusinessGaussian processcomputerSoftware1707description
This paper presents an approach for the simultaneous learning and recognition of places applied to autonomous robotics. While noteworthy results have been achieved with respect to off-line training process for appearance-based navigation, novel issues arise when recognition and learning are simultaneous and unsupervised processes. The approach adopted here uses a Gaussian mixture model estimated by a novel incremental MML-EM to model the probability distribution of features extracted by image-preprocessing. A place detector decides which features belong to which place integrating odometric information and a hidden Markov model. Tests demonstrate that the proposed system performs as well as the ones relying on batch off-line environmental learning. ©2007 IEEE.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2007-10-01 |