Abstract : This paper presents a complete framework for image-based navigation from an image memory that exploits mutual information and does not need any feature extraction, matching or any 3D information. The navigation path is represented by a set of automatically selected key images obtained during a prior learning phase. The shared information (entropy) between the current acquired image and nearby key images is exploited to switch key images during navigation. Based on the key images and the current image, the control law proposed by [1] is used to compute the rotational velocity of a mobile robot during its qualitative visual navigation. Using our approach, real-time navigation has been performed inside a corridor and inside a room with a Pioneer 3-DX equipped with an on-board perspective camera without the need of accurate mapping and localization.
Type de document :
Communication dans un congrès
IEEE Int. Conf. on Control, Automation, Robotics and Vision, ICARCV 2016, Nov 2016, Phuket, Thailand. IEEE Int. Conf. on Control, Automation, Robotics and Vision, ICARCV 2016, 2016
https://hal.inria.fr/hal-01355382
Contributeur : Eric Marchand
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Soumis le : mardi 23 août 2016 - 10:41:05
Dernière modification le : mercredi 16 mai 2018 - 11:23:03
Document(s) archivé(s) le : jeudi 24 novembre 2016 - 12:33:05
Suman Raj Bista, Paolo Robuffo Giordano, François Chaumette. Appearance-based Indoor Navigation by IBVS using Mutual Information. IEEE Int. Conf. on Control, Automation, Robotics and Vision, ICARCV 2016, Nov 2016, Phuket, Thailand. IEEE Int. Conf. on Control, Automation, Robotics and Vision, ICARCV 2016, 2016. 〈hal-01355382〉
