Published: October 31, 2018
Joseph A. Falco, Karl Van Wyk, Elena R. Messina
Increasing the flexibility and general-purpose applicability of robots is a longstanding goal. Several avenues of research are addressing these goals, ranging from integration of multiple sensors to allow robots to perceive their surroundings and adapt accordingly, to more sophisticated control algorithms that enable robots to re-plan based on current status, to development of more dexterous means of manipulating objects. As part of the manipulation thrust, there has been a recent increase in the development of robotic hands. Inspired by nature, these end effectors hold potential for allowing robots to pick up and manipulate a broader range of objects, without requiring customized end-of-arm tooling or grippers. With this rapidly-growing number of robot hands with diverse designs, there is a need to capture their individual competencies and characteristics under a unified framework. In addition to knowledge of basic hand characteristics such as the number of fingers, degrees of freedom, and degrees of actuation, performance metrics can provide valuable insight into not only the raw traits of the technology, but also their task and function-level performance capabilities. These measures can then be used to help match capabilities to end-user needs as well as provide researchers and developers insight for improving their hardware and software designs. This is a working document where periodic updates will be made based on public comment and lessons-learned from exercising the test methods.
Citation: Special Publication (NIST SP) - 1227 (Draft)Report Number:
NIST Pub Series: Special Publication (NIST SP)
Pub Type: NIST Pubs
Robotic Grasping, Dexterous Manipulation
Created October 31, 2018, Updated November 10, 2018