Learning Tethered Perching for Aerial Robots
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 300Wh 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 degrees 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.
WOS:001036713001018
Imperial College London
University of Bristol
Imperial College London
Centre National de la Recherche Scientifique (CNRS)
Imperial College London
University of Oxford
Imperial College London
École Polytechnique Fédérale de Lausanne
2023-01-01
New York
979-8-3503-2365-8
2023-May
IEEE International Conference on Robotics and Automation ICRA
1050-4729
2577-087X
1298
1304
REVIEWED
OTHER
| Event name | Event acronym | Event place | Event date |
London, ENGLAND | 2023-05-29 - 2023-06-02 | ||
| Funder | Funding(s) | Grant Number | Grant URL |
UK Research & Innovation (UKRI) | EP/N018494/1;EP/R026173/1;EP/R009953/1;EP/S031464/1;EP/W001136/1 | ||
UK Research & Innovation (UKRI) | NE/R012229/1 | ||
EU H2020 AeroTwin project | 810321 | ||
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