We are hoping to get your feedback on your measurement science and standards needs so that NIST can help industry even more with their robot challenges.
Our current Measurement Science for Manufacturing Robotics program is divided into seven projects:
- Agility Performance of Robotics Systems - Deliver robot agility performance metrics, test methods. information models, data sets, and planning approaches that will enable manufacturers to more easily and rapidly reconfigure and re-task robot systems
- Embodied AI and Data Generation for Manufacturing Robotics - To provide structured artificial intelligence (AI) and machine learning (ML) training datasets, and proven, trained, and applied AI/ML models to improve the performance and autonomy of manufacturing robotic applications.
- Grasping, Manipulation, and Contact Safety Performance of Robotic Systems - To provide performance metrics, test methods and associated measurement tools to support next-generation robot systems having human-like dexterity and force control characteristics that enable tactual-based safe human collaboration and manufacturing tasks.
- Mobility Performance of Robotic Systems - Provide the measurement science to develop standard test methods for intelligent industrial mobility systems, including mobile robots, mobile manipulators, and exoskeletons.
- Perception Performance of Robotic Systems - To develop measurement science for sensing and perception system performance characterization to reduce the risk related to the adoption of new technologies and to advance the agility, safety, and productivity of collaborative industrial and mobile robots.
- Performance of Human-Robot Interaction - To deliver a suite of test methods, protocols, and information models to enable effective, human-robot collaboration in manufacturing, and advance interactive robot technologies to facilitate the safe and efficient teaming of people and robots.
- Tools for Collaborative Robotics within SME Workcells - Deliver a suite of tools to mitigate the lack of automation and technical expertise that currently prevents small and medium manufacturers from adopting robotic systems.
We have produced / been involved with a number of outputs that we have seen improve manufacturing robotic system performance, collaboration, agility, autonomy, safety, and ease of implementation to enhance U.S. innovation and industrial competitiveness. Some of them include:
- Various Competitions: Agile Robotics for Industrial Automation Competition, Robotic Grasping and Manipulation Competition
- Data Sets: Peg in Hole Data, Mobile Manipulator Performance Measurement Data, 3D Data for the Evaluation of Point-Based Rigid Body Registration Error
- Test Methods: Grasp Metrics and Test Methods, Assembly Test Methods
- (Formal and De Facto) Standards: IEEE Core Ontology for Robotics and Automation Standard, Canonical Robot Command Language
- Standards Groups: ASTM F45 – Industrial Vehicle Performance Standards, ASTM F48 on Exoskeletons and Exosuits, ASTM E57 on 3D Imaging, IEEE RAS Robot Task Representation, IEEE RAS Robot Agility, IEEE RAS Grasp Performance Standards, IEEE RAS Metrology for Human-Robot Interaction
- Software/Tools/Artifacts: Tools for Collaborative Robots in SME Workcells, Assembly Task Boards
While we are very proud of what the program has accomplished, we want to see what we can do even better. We would love to get your feedback on your measurement science and standards needs so that NIST can help industry even more with their robot challenges.
Please provide feedback to Craig Schlenoff at craig.schlenoff [at] nist.gov.
Thanks and stay safe!
Measurement Science for Manufacturing Robotics Program Manager