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Search Publications by: Jeremy Marvel (Fed)

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Displaying 51 - 75 of 142

State-of-the-Art in Human-Robot Interaction

June 7, 2018
Author(s)
Jeremy Marvel, Megan Zimmerman, Shelly Bagchi
In this chapter, we will discuss the applications of HRI and HMI in industrial robotics, and will discuss topics such as collaborative robot safety, advances in HMI designs and development paradigms, and the current state of HRI. Throughout the following

Multi-Robot Assembly Strategies and Metrics

January 26, 2018
Author(s)
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
Author(s)
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

November 30, 2017
Author(s)
Jeremy 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

Using Sensor Feedback to Accurately Estimate Part Pose in Gripper

September 28, 2017
Author(s)
Nithyananda Bhat Kumbla, Jeremy Marvel, Satyandra K. Gupta
High volume manufacturing use custom made fixtures during assembly operations. Small volume manufacturing cannot use fixtures in order to keep setup time and production cost low. The performance of the task in fixture-less assemblies depends on the

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

February 10, 2017
Author(s)
Benjamin Y. Choo, Brian Weiss, Jeremy 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