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Search Publications by Jeremy Marvel

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Displaying 1 - 25 of 53

Technology Readiness Levels for Randomized Bin Picking, Performance Metrics for Intelligent Systems (PerMIS) 2012 Workshop, Special Session

February 8, 2021
Jeremy Marvel, Roger D. Eastman, Geraldine S. Cheok, Kamel S. Saidi, Tsai H. Hong, Elena R. Messina, Bob Bollinger, Paul Evans, Joyce Guthrie, Eric Hershberger, Carlos Martinez, Karen McNamara, James Wells
The special session on Technology Readiness Levels (TRLs) for Randomized Bin Picking was held during the morning session of the 2012 Performance Metrics for Intelligent Systems (PerMIS) workshop, 21 March, 2012. The stated objective of the special session

Workshop Report: Test Methods and Metrics for Effective HRI in Real-World Human-Robot Teams, ACM/IEEE Human-Robot Interaction Conference, 2020 (Virtual)

February 8, 2021
Shelly Bagchi, Jeremy Marvel, Megan L. Zimmerman, Murat Aksu, Brian Antonishek
This report details the second annual, full-day workshop exploring the metrology necessary for repeatably and independently assessing the performance of robotic systems in real-world human-robot interaction (HRI) scenarios. This workshop continues the

Workshop Report: Test Methods and Metrics for Effective HRI in Collaborative Human-Robot Teams, ACM/IEEE Human-Robot Interaction Conference, 2019

December 28, 2020
Shelly Bagchi, Murat Aksu, Megan L. Zimmerman, Jeremy Marvel, Brian Antonishek
Verified and validated test methods, being necessary to measure the performance of complex systems, are important tools for driving innovation, benchmarking and improving performance, and establishing trust in collaborative human-robot teams. This full-day

Improving 3D Vision-Robot Registration for Assembly Tasks

April 3, 2020
Marek Franaszek, Geraldine S. Cheok, Karl Van Wyk, Jeremy A. Marvel
Quality registration between the coordinate frames of a perception system and a robot is important for the efficient operation of autonomous systems in vision-guided assembly lines. Rigid-body registration, which is based on the measurement of

Reducing Localization Error of Vision-Guided Industrial Robots

June 18, 2019
Marek Franaszek, Geraldine S. Cheok, Jeremy A. Marvel
In many manufacturing applications, such as automated drilling or inspection of large parts, accurate knowledge of both position and orientation is critical. In this paper, a method for reducing robot end-effector position and orientation error is

Empowering Robotics in Manufacturing Through Metrology

December 3, 2018
Jeremy A. Marvel, Elena R. Messina
This paper discusses the challenges and opportunities surrounding robotics, as faced by the manufacturing industry. The means by which metrology can address these challenges and opportunities are also discussed. Details are given regarding NIST's Robotic

Stochastic Search Methods for Mobile Manipulators

November 30, 2018
Amoako-Frimpong Samuel Yaw, Matthew Messina, Henry Medeiros, Jeremy A. Marvel, Roger V. Bostelman
Mobile manipulators are a potential solution to the increasing need for additional flexibility and mobility in industrial applications. However, they tend to lack the accuracy and precision achieved by fixed manipulators, especially in scenarios where both

Multi-Robot Assembly Strategies and Metrics

January 26, 2018
Jeremy A. Marvel, Roger V. Bostelman, Joseph A. Falco
We present a survey of multi-robot assembly applications and methods, and describe trends and general insights into the multi-robot assembly problem for industrial applications. We focus on fixtureless assembly strategies featuring two or more robotic

Strategies for Improving Robot Registration Performance

January 26, 2018
Karl Van Wyk, Jeremy A. Marvel
The ability to calculate rigid-body transformations between arbitrary coordinate systems (i.e., registration) is an invaluable tool in robotics. This effort builds upon previous work by investigating strategies for improving the registration accuracy

Sensors for Safe, Collaborative Robots in Smart Manufacturing

December 1, 2017
Jeremy A. Marvel
The U.S. National Institute of Standards and Technology (NIST) is developing performance metrics for collaborative robotic systems for smart manufacturing applications. Using a suite of sensor platforms, feedback mechanisms, and novel test artifacts, NIST

Adaptive Multi-scale Prognostics and Health Management for Smart Manufacturing Systems

February 10, 2017
Benjamin Y. Choo, Brian A. Weiss, Jeremy A. Marvel, Stephen C. Adams, Peter A. Beling
Adaptive Multi-scale Prognostics and Health Management (AM-PHM) is a methodology designed to enable PHM in smart manufacturing systems. As a rule, PHM information is not yet fully utilized in higher-level decision-making in manufacturing systems. AM-PHM

Planning Algorithms for Multi-Setup Multi-Pass Robotic Cleaning with Oscillatory Moving Tools

November 17, 2016
Ariyan M. Kabir, Joshua D. Langsfeld, Shaurya Shriyam, Vinaichandra S. Rachakonda, Cunbo Zhuang, Krishnanand N. Kaipa, Jeremy A. Marvel, Satyandra K. Gupta
We describe planning algorithms for cleaning stains on a curved object. Removing the stain may require multiple reorientations of the part and some portions of the stain may require multiple cleaning passes. The experimental setup involves two robot arms

Enhancing Robotic Unstructured Bin-Picking Performance by Enabling Remote Human Interventions in Challenging Perception Scenarios

August 24, 2016
Krishnanand N. Kaipa, Akshaya S. Kankanhalli-Nagendra, Nithyananda B. Kumbla, Shaurya Shriyam, Srudeep Somnaath Thevendria-Karthic, Jeremy A. Marvel, Satyandra K. Gupta
We present an approach that enables a robot to initiate a call to a remote human operator and ask help in resolving automated perception system failures during bin- picking operations. Our approach allows a robot to evaluate the quality of part recognition

Implementing Speed and Separation Monitoring in Collaborative Robot Workcells

August 1, 2016
Jeremy A. Marvel, Richard J. Norcross
We provide an overview and guidance for the speed and separation monitoring methodology as presented in the International Organization of Standardization's technical specification 15066 on collaborative robot safety. Such functionality is provided by

Survey of Research for Performance Measurement of Mobile Manipulators

June 30, 2016
Roger V. Bostelman, Tsai H. Hong, Jeremy A. Marvel
This survey provides the basis for developing research in the area of mobile manipulator performance measurement, an area that has relatively few research articles, as com-pared to other mobile manipulator research areas. The survey begins with a