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Engineering Laboratory

## Intelligent Systems Division

-  Robotic Grasping and Manipulation for Assembly  Expand or Collapse    -  Grasping Performance Metrics and Test Methods 
  -  Assembly Performance Metrics and Test Methods 
  -  Robotic Grasping and Manipulation Competition: Manufacturing Track (RGMC)  Expand or Collapse      -  RGMC: Practice Task Board 
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# Grasping Performance Metrics and Test Methods

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## Summary

With a growing number of robot hands, there is an increasing 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 to match capabilities to end-user needs as well as to help provide researchers and developers insight for improving their hardware and software designs.

Robotic Hand Performance Testing

## Description

In order to design relevant performance metrics and methods for characterizing robotic hands, it helps to understand the issues surrounding robotic grasping and manipulation. Regardless of the actual task at hand, any grasping and manipulation problem can be broken down into its first principles, kinematics and kinetics, or more simply, motion and effort. Kinetics are the forces acting on bodies or particles that are responsible for causing their motion. In particular, any kinetic metric or test method will be evaluating force, torques, and any other measure of effort such as electrical current. Kinematics is the geometry of motion of bodies or particles with complete disregard for the forces that cause such motion. Therefore, any kinematic metric or test method will be concerned with evaluating positions, velocities, or accelerations of bodies, parts, or particles, and will typically be in units of length and time. Candidate entities of interest include palms, fingers, points of contact, or parts under grasp. Building test methods from this fundamental point of view will ultimately lead to relevant performance capture, and will span from lower-level capabilities including primitive sensing and control to higher-level capabilities including manipulation, perception, and decision making

When evaluating the capabilities of a robotic hand, performance tests should be agnostic to the other system components such as the robot arm and perception system. While it is possible to access data directly from a robotic hand and derive the defined metrics, these measurements would be based on the inherent properties of the system under test. Therefore, independent measurement systems must be developed to support testing to allow for comparative metrics between systems to establish extrinsic ground truths.

## **Preliminary Performance Metrics**

The table below contains links to the proposed metrics and test methods. Select the name of each grasp metric to download the MS Word document. Each file contains the grasp metric/test method description and example implementations using robotic hand technology. Each MS Word document also contains a link to a downloadable zip file containing the raw data collected. This video is a compilation of the test methods outlined below.	 

## **Disclaimer**

Certain commercial equipment, instruments, or materials are identified in this paper to foster understanding. Such identification does not imply recommendation or endorsement by the National Institute of Standards and Technology, nor does it imply that the materials or equipment identified are necessarily the best available for the purpose.

ManufacturingRobotics in manufacturing

-  **‹** Robotic Grasping and Manipulation for Assembly 
-  Assembly Performance Metrics and Test Methods **›** 

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