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NIST Robotics Wares: What You Can Use or Get Involved With Now
Agile Robotics for Industrial Automation Competition
Description: Simulation (Gazebo)-based competition whose core focus is to test the agility of industrial robot systems, with the goal of enabling industrial robots on the shop floors to be more productive, more autonomous, and to require less time from shop floor workers. Agility is defined as failure identification and recovery, automated planning and re-planning, and the ability to swap in and out different brand robots.
State of Maturity: We are currently in year five of the competition. First prize will be $10,000, second prize will be $5,000, and third prize will be $2,500.
Web Page: http://www.nist.gov/ariac/
Contact: Craig Schlenoff, 301-975-3456, craig.schlenoff [at] nist.gov (craig[dot]schlenoff[at]nist[dot]gov)
Assembly Test Methods
Description: This web site houses a set of performance metrics, test methods and associated artifacts that are being developed to evaluate robotic assembly systems. Test methods include task-level evaluation of gripper solutions using peg-in-hole artifacts and assembly fastener task boards for benchmarking different systems.
State of Maturity: The metrics, test methods, and related artifacts are being disseminated to allow researchers, developers, and intended users of assembly robotic systems to experiment with them and provide feedback on how to improve the procedures.
Contact: Joe Falco, 301-975-3455, joseph.falco [at] nist.gov (joseph[dot]falco[at]nist[dot]gov)
Canonical Robot Command Language
Description: The canonical robot command language (CRCL) is a robot-agnostic low-level messaging language for sending commands to, and receiving status from a robot. CRCL commands are executed by a low-level device controller. CRCL is intended primarily to provide commands that are independent of the kinematics of the robot that executes the commands.
State of Maturity: Used in NIST projects and at Georgia Tech Research Institute
Web Page: https://www.nist.gov/el/intelligent-systems-division-73500/canonical-robot-command-language-crcl
Contact: John Michaloski, 301-975-3458, john.michaloski [at] nist.gov (john[dot]michaloski[at]nist[dot]gov)
Core Ontology for Robotics and Automation
Description: A core ontology that specifies the main, most general concepts, relations, and axioms of robotics and automation (R&A), which is intended as a reference for knowledge representation and reasoning in robots, as well as a formal reference vocabulary for communicating knowledge about R&A between robots and humans.
State of Maturity: IEEE International Standard used by academic institutions and companies around the world
Web Page: https://standards.ieee.org/develop/wg/ORA.html
Contact: Craig Schlenoff, 301-975-3456, craig.schlenoff [at] nist.gov (craig[dot]schlenoff[at]nist[dot]gov)
Grasp Metrics and Test Methods
Description: This web site contains descriptions of metrics that can be used to characterize elemental performance of robotic hands, along with draft test methods that have been developed for these metrics. Datasets collected from experiments using the draft test methods are available for downloads, as well as designs for replicating the testing artifacts.
State of Maturity: The metrics, test methods, and related artifacts are being disseminated to allow researchers, developers, and intended users of advanced robotic hands to experiment with them and provide feedback on how to improve the procedures.
Contact: Joe Falco, 301-975-3455, joseph.falco [at] nist.gov (joseph[dot]falco[at]nist[dot]gov)
Performance Analytics Software
Description: Downloadable software that can assist in evaluating data to analyze results from experiments. Algorithms support analysis of attribute, ordinal, and continuous data.
State of Maturity: The algorithms have been used within NIST to support performance evaluation tests and are considered to be mature.
Web Page: https://www.nist.gov/el/intelligent-systems-division-73500/performance-data-analytics
Contact: Joe Falco, 301-975-3455, joseph.falco [at] nist.gov (joseph[dot]falco[at]nist[dot]gov)
Datasets
Dataset: 3D Data for the Evaluation of Point-Based, Rigid Body Registration Error
Description: Datasets to evaluate the performance of point-based, rigid-body registration may be downloaded from this site. Registration is the process of transforming one coordinate frame to another coordinate frame. The datasets contain 3D position measurements from three instruments: a laser tracker, a motion capture system (optical tracking system), and a large-scale metrology system.
State of Maturity: The datasets have been validated.
Contact: Marek Franaszek, 301-975-6408, marek.franaszek [at] nist.gov (marek[dot]franaszek[at]nist[dot]gov)
Dataset: Mobile Manipulator Performance Measurement Data
Description: This site contains data collected from experiments involving the positional accuracy of a mobile manipulator, comprised of an industrial robot arm mounted on an Automatic Guided Vehicle (AGV). Reference (also referred to as “ground truth”) position measurements captured from an optical tracking system are included to enable comparisons.
State of Maturity: The datasets have been validated
Contact: Ann Virts, 301-975-5068, ann.virts [at] nist.gov (ann[dot]virts[at]nist[dot]gov)
Dataset: Peg-in-Hole Data
Description: Data and results from three peg-in-hole experiments for improving insertion tasks may be downloaded from this site. A method was developed to reduce the point-based registration error by restoring the rigid body condition (RRBC method). Registration is the process of transforming one coordinate frame to another coordinate frame. The coordinate frame from which points are transformed is called the working frame and the coordinate frame to which points are transformed is called the destination frame. The RRBC method can be used to reduce the uncertainty of a hole location and thus, improve the success rate for insertion tasks. Peg-in-hole experiments were conducted to quantify the level of improvement.
State of Maturity: The datasets have been validated
Website: https://www.nist.gov/el/intelligent-systems-division-73500/peg-hole-data
Contact: Kam Saidi, 301-975-6069, kamel.saidi [at] nist.gov (kamel[dot]saidi[at]nist[dot]gov)