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Energy-Optimized Planning in Non-Uniform Wind Fields with Fixed-Wing Aerial Vehicles
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Robotics, Perception and Learning, RPL. ETH Zürich, Autonomous Systems Lab, Zürich, Switzerland, 8092.ORCID iD: 0009-0000-3233-4783
ETH Zürich, Autonomous Systems Lab, Zürich, Switzerland, 8092.
ETH Zürich, Autonomous Systems Lab, Zürich, Switzerland, 8092.
ETH Zürich, Autonomous Systems Lab, Zürich, Switzerland, 8092.
2024 (English)In: 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2024, Institute of Electrical and Electronics Engineers (IEEE) , 2024, p. 3116-3122Conference paper, Published paper (Refereed)
Abstract [en]

Fixed-wing small uncrewed aerial vehicles (sUAVs) possess the capability to remain airborne for extended durations and traverse vast distances. However, their operation is susceptible to wind conditions, particularly in regions of complex terrain where high wind speeds may push the aircraft beyond its operational limits, potentially raising safety concerns. Moreover, wind impacts the energy required to follow a path, especially in locations where the wind direction and speed are not favorable. Incorporating wind information into mission planning is essential to ensure both safety and energy efficiency. In this paper, we propose a sampling-based planner using the kinematic Dubins aircraft paths with respect to the ground, to plan energy-efficient paths in non-uniform wind fields. We study the characteristics of the planner with synthetic and real-world wind data and compare its performance against baseline cost and path formulations. We demonstrate that the energy-optimized planner effectively utilizes updrafts to minimize energy consumption, albeit at the expense of increased travel time. The ground-relative path formulation facilitates the generation of safe trajectories onboard sUAVs within reasonable computational timeframes.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2024. p. 3116-3122
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering Vehicle and Aerospace Engineering Robotics and automation
Identifiers
URN: urn:nbn:se:kth:diva-359874DOI: 10.1109/IROS58592.2024.10801294ISI: 001411890000331Scopus ID: 2-s2.0-85216457861OAI: oai:DiVA.org:kth-359874DiVA, id: diva2:1937183
Conference
2024 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2024, Abu Dhabi, United Arab Emirates, Oct 14 2024 - Oct 18 2024
Note

Part of ISBN 979-8-3503-7770-5

QC 20250213

Available from: 2025-02-12 Created: 2025-02-12 Last updated: 2025-04-28Bibliographically approved

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Duan, Yufei

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