Situational adaptive motion prediction for firefighting squads in indoor search and rescue

  • Firefighting is a complex, yet low automated task. To mitigate ergonomic and safety related risks on the human operators, robots could be deployed in a collaborative approach. To allow human-robot teams in firefighting, important basics are missing. Amongst other aspects, the robot must predict the human motion as occlusion is ever-present. In this work, we propose a novel motion prediction pipeline for firefighters' squads in indoor search and rescue. The squad paths are generated with an optimal graph-based planning approach representing firefighters' tactics. Paths are generated per room which allows to dynamically adapt the path locally without global re-planning. The motion of singular agents is simulated using a modification of the headed social force model. We evaluate the pipeline for feasibility with a novel data set generated from real footage and show the computational efficiency.

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Metadaten
Author:Nils MandischerORCiDGND, Frederik Schicks, Burkhard Corves
URN:urn:nbn:de:bvb:384-opus4-1178668
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/117866
URL:https://motionpredictionicra2023.github.io/proceedings.html
Parent Title (English):5th Workshop on Long-term Human Motion Prediction (LHMP), 2023 IEEE International Conference on Robotics and Automation (ICRA 2023), 29 May 2023, London, UK
Publisher:github
Editor:Andrey Rudenko, Luigi Palmieri
Type:Conference Proceeding
Language:English
Date of Publication (online):2025/01/02
Year of first Publication:2023
Publishing Institution:Universität Augsburg
Release Date:2025/01/07
Edition:Online-Ressource
DOI:https://doi.org/10.48550/arXiv.2306.02705
Institutes:Fakultät für Angewandte Informatik
Fakultät für Angewandte Informatik / Institut für Informatik
Fakultät für Angewandte Informatik / Institut für Informatik / Lehrstuhl für Ingenieurinformatik mit Schwerpunkt Mechatronik
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 60 Technik / 600 Technik, Technologie
Licence (German):CC-BY 4.0: Creative Commons: Namensnennung

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