Semantic path planning for indoor navigation and household tasks
Sun, Nico and Yang, Erfu and Corney, Jonathan and Chen, Yi; Althoefer, Kaspar and Konstantinova, Jelizaveta and Zhang, Ketao, eds. (2019) Semantic path planning for indoor navigation and household tasks. In: Towards Autonomous Robotic Systems. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) . Springer-Verlag, GBR, pp. 191-201. ISBN 9783030253318 (https://doi.org/10.1007/978-3-030-25332-5_17)
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Abstract
Assisting people with daily living tasks in their own homes with a robot requires a navigation through a cluttered and varying environment. Sometimes the only possible path would be blocked by an obstacle which needs to be moved away but not into other obstructing regions like the space required for opening a door. This paper presents semantic assisted path planning in which a gridded semantic map is used to improve navigation among movable obstacles (NAMO) and partially plan simple household tasks like cleaning a carpet or moving objects to another location. Semantic planning allows the execution of tasks expressed in human-like form instead of mathematical concepts like coordinates. In our numerical experiments, spatial planning was completed well within a typical human-human dialogue response time, allowing for an immediate response by the robot.
ORCID iDs
Sun, Nico, Yang, Erfu ORCID: https://orcid.org/0000-0003-1813-5950, Corney, Jonathan ORCID: https://orcid.org/0000-0003-1210-3827 and Chen, Yi; Althoefer, Kaspar, Konstantinova, Jelizaveta and Zhang, Ketao-
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Item type: Book Section ID code: 73598 Dates: DateEvent17 July 2019Published1 April 2019AcceptedSubjects: Science > Mathematics > Electronic computers. Computer science Department: Faculty of Engineering > Design, Manufacture and Engineering Management
Strategic Research Themes > Innovation EntrepreneurshipDepositing user: Pure Administrator Date deposited: 13 Aug 2020 14:07 Last modified: 20 Dec 2024 01:08 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/73598