Intent-driven strategic tactical planning for autonomous site inspection using cooperative drones
Buksz, Dorian and Mujumdar, Anusha and Orlić, Marin and Mohalik, Swarup and Daoutis, Marios and Badrinath, Ramamurthy and Magazzeni, Daniele and Cashmore, Michael and Feljan, Anerta Vulgarakis; (2021) Intent-driven strategic tactical planning for autonomous site inspection using cooperative drones. In: 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2020. IEEE International Conference on Intelligent Robots and Systems . IEEE, Piscataway, N.J., pp. 6733-6740. ISBN 9781728162126 (https://doi.org/10.1109/IROS45743.2020.9341440)
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Abstract
Realization of industry-scale, goal-driven, autonomous systems with AI planning technology faces several challenges: flexibly specifying planning goal states in varying situations, synthesizing plans in large state spaces, re-planning in dynamic situations, and facilitating humans to supervise, give feedback and intervene. In this paper, we present Intent-driven Strategic Tactical Planning (ISTP) to address these challenges. We demonstrate its efficacy through its application for radio base station inspection across several locations using drones. The inspection task involves capturing images, thermal images or signal measurements - called knowledge-objects - of various components of the base stations for downstream processing. In the ISTP approach, an operator indicates her goals by flying the drone to different components of interest. These goals are generalized to capture the intent of the operator, which are then instantiated in new situations to generate goals dynamically. Towards planning and re-planning in large state spaces to achieve these goals efficiently, we extend the Strategic-Tactical Planning paradigm. All the components of ISTP are integrated in an intuitive UI and demonstrated through a real life use-case built on the UNITY simulator platform.
ORCID iDs
Buksz, Dorian, Mujumdar, Anusha, Orlić, Marin, Mohalik, Swarup, Daoutis, Marios, Badrinath, Ramamurthy, Magazzeni, Daniele, Cashmore, Michael ORCID: https://orcid.org/0000-0002-8334-4348 and Feljan, Anerta Vulgarakis;-
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Item type: Book Section ID code: 73423 Dates: DateEvent10 February 2021Published1 July 2020AcceptedNotes: © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Subjects: Technology > Electrical engineering. Electronics Nuclear engineering Department: Faculty of Science > Computer and Information Sciences Depositing user: Pure Administrator Date deposited: 03 Aug 2020 20:49 Last modified: 17 Nov 2024 01:31 URI: https://strathprints.strath.ac.uk/id/eprint/73423