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Survey of maps of dynamics for mobile robots
Mobile Robotics Group, School of Electrical Engineering, Aalto University, Finland; Finnish Center for Artificial Intelligence, Finland.ORCID iD: 0000-0002-9503-0602
Örebro University, School of Science and Technology. (Mobile Robots and Olfaction Lab, AASS)ORCID iD: 0000-0001-8658-2985
L-CAS, School of Computer Science, University of Lincoln, Lincoln, UK.
BOSCH Corporate Research, Renningen, Germany.
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2023 (English)In: The international journal of robotics research, ISSN 0278-3649, E-ISSN 1741-3176, Vol. 42, no 11, p. 977-1006Article in journal (Refereed) Published
Abstract [en]

Robotic mapping provides spatial information for autonomous agents. Depending on the tasks they seek to enable, the maps created range from simple 2D representations of the environment geometry to complex, multilayered semantic maps. This survey article is about maps of dynamics (MoDs), which store semantic information about typical motion patterns in a given environment. Some MoDs use trajectories as input, and some can be built from short, disconnected observations of motion. Robots can use MoDs, for example, for global motion planning, improved localization, or human motion prediction. Accounting for the increasing importance of maps of dynamics, we present a comprehensive survey that organizes the knowledge accumulated in the field and identifies promising directions for future work. Specifically, we introduce field-specific vocabulary, summarize existing work according to a novel taxonomy, and describe possible applications and open research problems. We conclude that the field is mature enough, and we expect that maps of dynamics will be increasingly used to improve robot performance in real-world use cases. At the same time, the field is still in a phase of rapid development where novel contributions could significantly impact this research area.

Place, publisher, year, edition, pages
Sage Publications, 2023. Vol. 42, no 11, p. 977-1006
Keywords [en]
mapping, maps of dynamics, localization and mapping, acceptability and trust, human-robot interaction, human-aware motion planning
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:oru:diva-107930DOI: 10.1177/02783649231190428ISI: 001042374800001Scopus ID: 2-s2.0-85166946627OAI: oai:DiVA.org:oru-107930DiVA, id: diva2:1792782
Funder
EU, Horizon 2020, 101017274
Note

Funding agencies:

Czech Ministry of Education by OP VVV CZ.02.1.01/0.0/0.0/16 019/0000765

Business Finland 9249/31/2021

 

Available from: 2023-08-30 Created: 2023-08-30 Last updated: 2024-01-03Bibliographically approved

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Magnusson, MartinSwaminathan, Chittaranjan SrinivasSchaffernicht, ErikLilienthal, Achim J.

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Kucner, Tomasz PiotrMagnusson, MartinSwaminathan, Chittaranjan SrinivasSchaffernicht, ErikBellotto, NicolaLilienthal, Achim J.
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The international journal of robotics research
Computer Vision and Robotics (Autonomous Systems)

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