Robot localization from minimalist inertial data using a Hidden Markov Model
Hidden Markov Models (HMM) are applied to interoceptive data (in this case the sense of rotation by way of a gyroscope) acquired by a moving wheeled robot when contouring an indoor environment. We demonstrate the soundness of HMM to solve the problem of robot localization in a topological model of t...
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| Format: | conferenceObject |
| Language: | eng |
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2014
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| Online Access: | http://hdl.handle.net/10400.26/6593 |
| Country: | Portugal |
| Oai: | oai:comum.rcaap.pt:10400.26/6593 |