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Herding by caging: a formation-based motion planning framework for guiding mobile agents
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Robotics, Perception and Learning, RPL.ORCID iD: 0000-0002-0900-1523
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Chemistry, Organic chemistry.ORCID iD: 0000-0002-9001-7708
KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for Autonomous Systems, CAS.ORCID iD: 0000-0003-2965-2953
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2021 (English)In: Autonomous Robots, ISSN 0929-5593, E-ISSN 1573-7527, Vol. 45, no 5, p. 613-631Article in journal (Refereed) Published
Abstract [en]

We propose a solution to the problem of herding by caging: given a set of mobile robots (called herders) and a group of moving agents (called sheep), we guide the sheep to a target location without letting them escape from the herders along the way. We model the interaction between the herders and the sheep by defining virtual “repulsive forces” pushing the sheep away from the herders. This enables the herders to partially control the motion of the sheep. We formalize this behavior topologically by applying the notion of caging, a concept used in robotic manipulation. We demonstrate that our approach is provably correct in the sense that the sheep cannot escape from the robots under our assumed motion model. We propose an RRT-based path planning algorithm for herding by caging, demonstrate its probabilistic completeness, and evaluate it in simulations as well as on a group of real mobile robots.

Place, publisher, year, edition, pages
Springer , 2021. Vol. 45, no 5, p. 613-631
Keywords [en]
Computational geometry, Motion and path planning, Path planning for multiple mobile robots or agents, Topological representation and abstraction of configuration spaces, Agricultural robots, Mobile robots, Robot programming, Motion modeling, Path-planning algorithm, Repulsive forces, Robotic manipulation, Target location, Mobile agents
National Category
Robotics and automation
Identifiers
URN: urn:nbn:se:kth:diva-307078DOI: 10.1007/s10514-021-09975-8ISI: 000627308100002Scopus ID: 2-s2.0-85102369985OAI: oai:DiVA.org:kth-307078DiVA, id: diva2:1631013
Note

QC 20220121

Available from: 2022-01-21 Created: 2022-01-21 Last updated: 2025-02-09Bibliographically approved

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Varava, AnastasiiaKravchenko, OleksandrKragic, DanicaPokorny, Florian T.

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Varava, AnastasiiaKravchenko, OleksandrKragic, DanicaPokorny, Florian T.
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Robotics, Perception and Learning, RPLOrganic chemistryCentre for Autonomous Systems, CAS
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Autonomous Robots
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