Closed-Structure Compliant Gripper With Morphologically Optimized Multi-Material Fingertips for Aerial Grasping
Loong Yi Lee, Omar Ali Syadiqeen Malik, Chee Pin Tan, Surya G. Nurzaman
Abstract
Aerial grasping empowers unmanned aerial vehicles to find applications beyond structured logistics. However, it brings a number of challenges including inaccurate positioning of the end effector and limited energy sources. Moreover, solutions so far have difficulty in handling a variety of objects. A novel closed structure compliant gripper was developed to address the challenges above. The gripper has a large self-centering work envelope and is normally-closed for passive grasping. Introduction of compliance as a form of morphological computation was also considered to enhance grasping capabilities, where multi-material 3D printing would facilitate rapid design changes based on target application. To grasp different objects, the gripper has hot-swappable 3D printed fingertips which are optimized with a multi-objective Bayesian Optimization process using physical bench experiments mimicking drone grasping and ascent on a common object set. The morphology of the fingertip including tip width, curvature and distribution of soft and hard material on contact surface, are optimized with a bench test that mimics quadcopter takeoff and landing. The best design from optimization shows an improvement of more than 10% from the initial design in successful grasp operations, demonstrated by field tests with a quadcopter.