Learning tethered perching for aerial robots
File(s)DronePerching.pdf (921.37 KB)
Accepted version
Author(s)
Type
Conference Paper
Abstract
Aerial robots have a wide range of applications, such as collecting data in hard-to-reach areas. This requires the longest possible operation time. However, because currently available commercial batteries have limited specific energy of roughly 300 W h kg -1 , a drone's flight time is a bottleneck for sustainable long-term data collection. Inspired by birds in nature, a possible approach to tackle this challenge is to perch drones on trees, and environmental or man-made structures, to save energy whilst in operation. In this paper, we propose an algorithm to automatically generate trajectories for a drone to perch on a tree branch, using the proposed tethered perching mechanism with a pendulum-like structure. This enables a drone to perform an energy-optimised, controlled 180° flip to safely disarm upside down. To fine-tune a set of reachable trajectories, a soft actor critic-based reinforcement algorithm is used. Our experimental results show the feasibility of the set of trajectories with successful perching. Our findings demonstrate that the proposed approach enables energy-efficient landing for long-term data collection tasks.
Date Issued
2023-07-04
Date Acceptance
2023-05-01
Citation
2023 IEEE International Conference on Robotics and Automation (ICRA), 2023, pp.1298-1304
Publisher
IEEE
Start Page
1298
End Page
1304
Journal / Book Title
2023 IEEE International Conference on Robotics and Automation (ICRA)
Copyright Statement
Copyright © 2023 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.
Identifier
http://dx.doi.org/10.1109/icra48891.2023.10161135
Source
2023 IEEE International Conference on Robotics and Automation (ICRA)
Publication Status
Published
Start Date
2023-05-29
Finish Date
2023-06-02
Coverage Spatial
London, UK