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Motion Planning Using MoDs
Örebro University, School of Science and Technology. (AASS Mobile Robotics & Olfaction Lab)ORCID iD: 0000-0002-9503-0602
Örebro University, School of Science and Technology. (AASS Mobile Robotics & Olfaction Lab)ORCID iD: 0000-0003-0217-9326
Örebro University, School of Science and Technology. (AASS Mobile Robotics & Olfaction Lab)ORCID iD: 0000-0001-8658-2985
Corporate Research, Robert Bosch GmbH, Renningen, Germany.
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2020 (English)In: Probabilistic Mapping of Spatial Motion Patterns for Mobile Robots, Springer, 2020, p. 115-141Chapter in book (Refereed)
Abstract [en]

Maps of dynamics can be beneficial for motion planning. Information about motion patterns in the environment can lead to finding flow-aware paths, allowing robots to align better to the expected motion: either of other agents in the environment or the flow of air or another medium. The key idea of flow-aware motion planning is to include adherence to the flow represented in the MoD into the motion planning algorithm’s sub-units (i.e. cost function, sampling mechanism), thereby biasing the motion planner into obeying local and implicit traffic rules. 

Place, publisher, year, edition, pages
Springer, 2020. p. 115-141
Series
Cognitive Systems Monographs, ISSN 1867-4925 ; 40
National Category
Robotics
Identifiers
URN: urn:nbn:se:oru:diva-81668DOI: 10.1007/978-3-030-41808-3_5Scopus ID: 2-s2.0-85083963960ISBN: 978-3-030-41807-6 (print)ISBN: 978-3-030-41808-3 (electronic)OAI: oai:DiVA.org:oru-81668DiVA, id: diva2:1430037
Available from: 2020-05-13 Created: 2020-05-13 Last updated: 2020-05-13Bibliographically approved

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Kucner, Tomasz PiotrLilienthal, AchimMagnusson, MartinSwaminathan, Chittaranjan Srinivas

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