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Evaluation of Reactive Obstacle Avoidance Algorithms for a Quadcopter
Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0003-3011-1505
Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering. (KPLAB)
Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
iRobot, Pasadena, CA, USA.
2016 (English)In: Proceedings of the 14th International Conference on Control, Automation, Robotics and Vision 2016 (ICARCV), IEEE conference proceedings, 2016, Tu31.3Conference paper, Published paper (Refereed)
Abstract [en]

In this work we are investigating reactive avoidance techniques which can be used on board of a small quadcopter and which do not require absolute localisation. We propose a local map representation which can be updated with proprioceptive sensors. The local map is centred around the robot and uses spherical coordinates to represent a point cloud. The local map is updated using a depth sensor, the Inertial Measurement Unit and a registration algorithm. We propose an extension of the Dynamic Window Approach to compute a velocity vector based on the current local map. We propose to use an OctoMap structure to compute a 2-pass A* which provide a path which is converted to a velocity vector. Both approaches are reactive as they only make use of local information. The algorithms were evaluated in a simulator which offers a realistic environment, both in terms of control and sensors. The results obtained were also validated by running the algorithms on a real platform.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2016. Tu31.3
Series
International Conference on Control Automation Robotics and Vision, ISSN 2474-2953
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:liu:diva-130956DOI: 10.1109/ICARCV.2016.7838803ISI: 000405520900204Scopus ID: 2-s2.0-85015170851ISBN: 9781509035496 (electronic)ISBN: 9781509047574 (electronic)ISBN: 9781509035502 (print)OAI: oai:DiVA.org:liu-130956DiVA: diva2:957288
Conference
14th International Conference on Control, Automation, Robotics and Vision (ICARCV), Phuket, Thailand, November 13-15, 2016
Note

Funding agencies:This work is partially supported by the Swedish Research Council (VR) Linnaeus Center CADICS, the ELLIIT network organization for Information and Communication Technology, and the Swedish Foundation for Strategic Research (CUAS Project, SymbiKCIoud Project).

Available from: 2016-09-01 Created: 2016-09-01 Last updated: 2017-08-09Bibliographically approved

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Citation style
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