An Open-Source Soft Robotic Platform for Autonomous Aerial Manipulation in the Wild

September 11, 2024 Β· Declared Dead Β· πŸ› Conference on Robot Learning

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Authors Erik Bauer, Marc BlΓΆchlinger, Pascal Strauch, Arman Raayatsanati, Curdin Cavelti, Robert K. Katzschmann arXiv ID 2409.07662 Category cs.RO: Robotics Cross-listed eess.SY Citations 8 Venue Conference on Robot Learning Repository https://github.com/raptor-ethz Last Checked 1 month ago
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 offboard 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 ROS 2 software stack and custom hardware design, making our contributions accessible to the broader research community.
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