eprintid: 42824 rev_number: 15 eprint_status: archive userid: 1903 dir: disk0/00/04/28/24 datestamp: 2016-07-13 15:40:34 lastmod: 2016-07-14 14:59:16 status_changed: 2016-07-13 15:40:34 type: conference_item metadata_visibility: show creators_name: Changhong, Fu creators_name: Carrio Fernández, Adrián creators_name: Campoy Cervera, Pascual creators_id: pascual.campoy@upm.es creators_orcid: 0000-0002-9894-2009 title: Efficient Visual Odometry and Mapping for Unmanned Aerial Vehicle Using ARM-based Stereo Vision Pre-Processing System ispublished: pub subjects: robotica note: Computer Vision Group (CVG) abstract: Visual odometry and mapping methods can provide accurate navigation and comprehensive environment (obstacle) information for autonomous flights of Unmanned Aerial Vehicle (UAV) in GPS-denied cluttered environments. This work presents a new light small-scale low-cost ARM-based stereo vision pre-processing system, which not only is used as onboard sensor to continuously estimate 6-DOF UAV pose, but also as onboard assistant computer to pre-process visual information, thereby saving more computational capability for the onboard host computer of the UAV to conduct other tasks. The visual odometry is done by one plugin specifically developed for this new system with a fixed baseline (12cm). In addition, the preprocessed infromation from this new system are sent via a Gigabit Ethernet cable to the onboard host computer of UAV for real-time environment reconstruction and obstacle detection with a octree-based 3D occupancy grid mapping approach, i.e. OctoMap. The visual algorithm is evaluated with the stereo video datasets from EuRoC Challenge III in terms of efficiency, accuracy and robustness. Finally, the new system is mounted and tested on a real quadrotor UAV to carry out the visual odometry and mapping task. date: 2015 date_type: published publisher: IEEE full_text_status: public pres_type: paper pagerange: 957-962 event_title: 2015 International Conference on Unmanned Aircraft Systems (ICUAS) event_location: Denver, Colorado, USA event_dates: June 9-12, 2015 event_type: conference institution: Industriales department: Automatica refereed: TRUE isbn: 978-1-4799-6009-5 book_title: 2015 International Conference on Unmanned Aircraft Systems (ICUAS) rights: by-nc-nd comprojects_type: FP7 comprojects_type: MINECO comprojects_code: 2010-20751- C02-01 comprojects_acronym: IRSES comprojects_title: UECIMUAVS: USA and Europe Cooperation in Mini UAVs comprojects_title: MeSOANTEN projec citation: Changhong, Fu, Carrio Fernández, Adrián and Campoy Cervera, Pascual ORCID: https://orcid.org/0000-0002-9894-2009 (2015). Efficient Visual Odometry and Mapping for Unmanned Aerial Vehicle Using ARM-based Stereo Vision Pre-Processing System. In: "2015 International Conference on Unmanned Aircraft Systems (ICUAS)", June 9-12, 2015, Denver, Colorado, USA. ISBN 978-1-4799-6009-5. pp. 957-962. document_url: https://oa.upm.es/42824/1/INVE_MEM_2015_231483.pdf