Grasp EveryThing (GET): 1-DoF, 3-Fingered Gripper with Tactile Sensing for Robust Grasping
Burgess, Michael, Adelson, Edward H.
–arXiv.org Artificial Intelligence
Grasp EveryThing (GET) Gripper . We demonstrate its capability in completing a variety of household tasks through teleoperation on the ALOHA system [1]. Abstract --We introduce the Grasp EveryThing (GET) gripper, a novel 1-DoF, 3-finger design for securely grasping objects of many shapes and sizes. Mounted on a standard parallel jaw actuator, the design features three narrow, tapered fingers arranged in a two-against-one configuration, where the two fingers converge into a V-shape. The GET gripper is more capable of conforming to object geometries and forming secure grasps than traditional designs with two flat fingers. Inspired by the principle of self-similarity, these V-shaped fingers enable secure grasping across a wide range of object sizes. Further to this end, fingers are parametrically designed for convenient resizing and interchangeability across robotic embodiments with a parallel jaw gripper . Additionally, we incorporate a rigid fingernail for ease in manipulating small objects. T actile sensing can be integrated into the standalone finger via an externally-mounted camera. A neural network was trained to estimate normal force from tactile images with an average validation error of 1.3 N across a diverse set of geometries. In grasping 15 objects and performing 3 tasks via teleoperation, the GET fingers consistently outperformed standard flat fingers. All finger designs, compatible with multiple robotic embodiments, both incorporating and lacking tactile sensing, are available on GitHub.
arXiv.org Artificial Intelligence
Aug-1-2025
- Country:
- Africa > Togo (0.04)
- North America > United States
- Indiana (0.04)
- Massachusetts > Middlesex County
- Cambridge (0.04)
- Genre:
- Research Report (0.50)
- Technology:
- Information Technology > Artificial Intelligence > Robots > Manipulation (1.00)