An Open-Source Soft Robotic Platform for Autonomous Aerial Manipulation in the Wild
Abstract
Aerial manipulation combines the versatility and speed of flying platforms with the functional capabilities of mobile manipulation, which presents significant challenges due to the need for precise localization and control. Traditionally, researchers have relied on off-board perception systems, which are limited to expensive and impractical specially equipped indoor environments. In this work, we introduce a novel platform for autonomous aerial manipulation that exclusively utilizes onboard perception systems. Our platform can perform aerial manipulation in various indoor and outdoor environments without depending on external perception systems. Our experimental results demonstrate the platform’s ability to autonomously grasp various objects in diverse settings. This advancement significantly improves the scalability and practicality of aerial manipulation applications by eliminating the need for costly tracking solutions. To accelerate future research, we open source our modern ROS 2 software stack and custom hardware design, making our contributions accessible to the broader research community.
Cite
Text
Bauer et al. "An Open-Source Soft Robotic Platform for Autonomous Aerial Manipulation in the Wild." Proceedings of The 8th Conference on Robot Learning, 2024.Markdown
[Bauer et al. "An Open-Source Soft Robotic Platform for Autonomous Aerial Manipulation in the Wild." Proceedings of The 8th Conference on Robot Learning, 2024.](https://mlanthology.org/corl/2024/bauer2024corl-opensource/)BibTeX
@inproceedings{bauer2024corl-opensource,
title = {{An Open-Source Soft Robotic Platform for Autonomous Aerial Manipulation in the Wild}},
author = {Bauer, Erik and Blöchlinger, Marc and Strauch, Pascal and Raayatsanati, Arman and Curdin, Cavelti and Katzschmann, Robert K.},
booktitle = {Proceedings of The 8th Conference on Robot Learning},
year = {2024},
pages = {3094-3106},
volume = {270},
url = {https://mlanthology.org/corl/2024/bauer2024corl-opensource/}
}