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Down the CLiFF: Flow-Aware Trajectory Planning under Motion Pattern Uncertainty
Örebro University, School of Science and Technology. (MRO, AASS)ORCID iD: 0000-0002-9545-9871
Örebro University, School of Science and Technology. (MRO, AASS)ORCID iD: 0000-0002-9503-0602
Örebro University, School of Science and Technology. (MRO, AASS)ORCID iD: 0000-0001-8658-2985
Robert Bosch, GmbH Corporate Research, Germany.ORCID iD: 0000-0002-4908-5434
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2018 (English)In: 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 7403-7409Conference paper, Published paper (Refereed)
Abstract [en]

In this paper we address the problem of flow-aware trajectory planning in dynamic environments considering flow model uncertainty. Flow-aware planning aims to plan trajectories that adhere to existing flow motion patterns in the environment, with the goal to make robots more efficient, less intrusive and safer. We use a statistical model called CLiFF-map that can map flow patterns for both continuous media and discrete objects. We propose novel cost and biasing functions for an RRT* planning algorithm, which exploits all the information available in the CLiFF-map model, including uncertainties due to flow variability or partial observability. Qualitatively, a benefit of our approach is that it can also be tuned to yield trajectories with different qualities such as exploratory or cautious, depending on application requirements. Quantitatively, we demonstrate that our approach produces more flow-compliant trajectories, compared to two baselines.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018. p. 7403-7409
Series
IEEE International Conference on Intelligent Robots and Systems, ISSN 2153-0858, E-ISSN 2153-0866
Keywords [en]
Trajectory, Robots, Planning, Cost function, Uncertainty, Veichle dynamics, Aerospace electronics
National Category
Robotics
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-70143DOI: 10.1109/IROS.2018.8593905ISI: 000458872706106ISBN: 978-1-5386-8094-0 (electronic)ISBN: 978-1-5386-8095-7 (print)OAI: oai:DiVA.org:oru-70143DiVA, id: diva2:1262737
Conference
31st IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain, October 1-5, 2018
Projects
ILIAD
Funder
EU, Horizon 2020, 732737Available from: 2018-11-12 Created: 2018-11-12 Last updated: 2019-03-14Bibliographically approved

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Down The CLiFF: Flow-aware Trajectory Planning under Motion Pattern Uncertainty(469 kB)63 downloads
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Swaminathan, Chittaranjan SrinivasKucner, Tomasz PiotrMagnusson, MartinLilienthal, Achim

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Swaminathan, Chittaranjan SrinivasKucner, Tomasz PiotrMagnusson, MartinPalmieri, LuigiLilienthal, Achim
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