Energy-aware planning-scheduling for autonomous aerial robots

Adam Seewald*, H.G. de Marina, Henrik Skov Midtiby, Ulrik Pagh Schultz Lundquist

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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In this paper, we present an online planning-scheduling approach for battery-powered autonomous aerial robots. The approach consists of simultaneously planning a coverage path and scheduling onboard computational tasks. We further derive a novel variable coverage motion robust to air-borne constraints and an empirically motivated energy model. The model includes the energy contribution of the schedule based on an automatic computational energy modeling tool. Our experiments show how an initial flight plan is adjusted online as a function of the available battery, accounting for uncertainty. Our approach remedies possible in-flight failure in case of unexpected battery drops, e.g., due to adverse atmospheric conditions, and increases the overall fault tolerance
Original languageEnglish
Title of host publicationProceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'22)
Publication date23. Oct 2022
Pages2946 - 2953
ISBN (Electronic)978-1-6654-7927-1
Publication statusPublished - 23. Oct 2022
Event2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS): Late Breaking Results Poster - Kyoto, Japan
Duration: 23. Oct 202227. Oct 2022


Conference2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
SeriesI E E E International Conference on Intelligent Robots and Systems. Proceedings


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