Learning to open new doors
Rattachement africain : us. Niveau de preuve : code pays fourni par la source.
Le résumé fourni par la source
We consider the problem of enabling a robot to autonomously open doors, including novel ones that the robot has not previously seen. Given the large variation in the appearances and locations of doors and door handles, this is a challenging perception and control problem; but this capability will significantly enlarge the range of environments that our robots can autonomously navigate through. In this paper, we focus on the case of doors with door handles. We propose an approach that, rather than trying to build a full 3d model of the door/door handle-which is challenging because of occlusion, specularity of many door handles, and the limited accuracy of our 3d sensors-instead uses computer vision to choose a manipulation strategy. Specifically, it uses an image of the door handle to identify a small number of “3d key locations,” such as the axis of rotation of the door handle, and the location of the end-point of the door-handle. These key locations then completely define a trajectory for the robot end-effector (hand) that successfully turns the door handle and opens the door. Evaluated on a large set of doors that the robot had not previously seen, it successfully opened 31 out of 34 doors. We also show that this approach of using vision to identify a small number of key locations also generalizes to a range of other tasks, including turning a thermostat knob, pulling open a drawer, and pushing elevator buttons.
Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.
Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Learning to open new doors
- Date Crossref
- 01/10/2010
- Éditeur
- IEEE
- Type
- proceedings-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Où se fait cette recherche
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Vaughn College of Aeronautics and Technology pays non établi dans la noticeUniversité ou école supérieure
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Stanford University Department of Aeronautics and Astronautics pays non établi dans la noticeUniversité ou école supérieure
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Cornell University pays non établi dans la noticeUniversité ou école supérieure
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University of Stanford Department of Aeronautics and Astronautics pays non établi dans la noticeUniversité ou école supérieure
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Faculty of Computer Science pays non établi dans la noticeUniversité ou école supérieure
Vaughn College of Aeronautics and Technology, Department of Aeronautics and Astronautics — Stanford University et Cornell University, avec 2 autres affiliations.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.