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MANIPULATION

RAPTOR: Rapid Aerial Pickup and Transport of Objects by Robots

Aurel X. Appius, Erik Bauer, Marc Blöchlinger, Aashi Kalra, Robin Oberson, Arman Raayatsanati, Pascal Strauch, Sarath Suresh, Marco von Salis, Robert K. Katzschmann

Year
2022
Citations
34

Abstract

Rapid aerial grasping through robots can lead to many applications that utilize fast and dynamic picking and placing of objects. Rigid grippers traditionally used in aerial manipulators require high precision and specific object geometries for successful grasping. We propose RAPTOR, a quadcopter platform combined with a custom Fin Ray <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">®</sup> gripper to enable more flexible grasping of objects with different geometries, leveraging the properties of soft materials to increase the contact surface between the gripper and the objects. To reduce the communication latency, we present a new lightweight middleware solution based on Fast DDS (Data Distribution Service) as an alternative to ROS (Robot Operating System). We show that RAPTOR achieves an average of 83% grasping efficacy in a real-world setting for four different object geometries while moving at an average velocity of 1 m/s during grasping. In a high-velocity setting, RAPTOR supports up to four times the payload compared to previous works. Our results highlight the potential of aerial drones in automated warehouses and other manipulation applications where speed, swiftness, and robustness are essential while operating in hard-to-reach places. <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> Code: https://github.com/raptor-ethz/raptor_setup

Keywords

QuadcopterDroneGrippersComputer scienceRobotPayload (computing)Robustness (evolution)Artificial intelligenceComputer visionComputer graphics (images)

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