Aide à la navigation pour les personnes handicapées : reconnaissance de trajets

Abstract : The work presented in this thesis concerns navigation assistance for a smart wheelchair. We propose a new approach based on this behaviour based structure, aiming at assisting the user in a global way. The intelligent system relies on a modelisation of the most frequently used routes and assists the user when navigating by suggesting the next movement when the route has been recognised. The user will not have to change the direction, thus sparing him/her an action. This work is included in the VAHM project that use commercial electric wheelchair which is enhanced by several sensors and a calculator. The VAHM project is using a multi-agent control system. Different behaviours (direction following, wall following, obstacle avoidance ...) are designed react to the environment. At first, we tried to modelize and recognize behaviour sequences with HMM. This method showed its limits to generalize the recognition of unlearned trajectories. Then we used M-HMM (by adding sensor?s data) to achieve recognition. However, our tests show that the recognition is better by using only sensor?s data. These observations have conducted us to use only sensor?s data for the recognition. The CONDENSATION algorithm had been tested to perform recognition from sensor's data. This system earn numerous advantages including that it doesn?t need a complex model since only one reference trajectory is necessary to perform the recognition. Then these trajectory models have been put into a Bayesian network to facilitate transitions between models in order to recognize a long trajectory. The last part of this thesis presents recognition?s results in real conditions on the VAHM 3 wheelchair prototype
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Régis Grasse. Aide à la navigation pour les personnes handicapées : reconnaissance de trajets. Autre. Université Paul Verlaine - Metz, 2007. Français. ⟨NNT : 2007METZ040S⟩. ⟨tel-01752870⟩

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