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Search Publications by: Jeremy Marvel ()

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Displaying 1 - 25 of 73

The Need for Reproducible Research in Soft Robotics

July 16, 2024
Author(s)
Andrew Spielberg, Jeremy Marvel, Dylan Shah, Jennifer Case, Robert Baines
To avoid facing a reproducibility crisis that will undermine the recent rapid pace of research and hamper widespread adoption, the field of soft robotics needs to establish best practices and uphold rigorous reporting.

Preliminary Study of Mixed Reality Interfaces for Collaborative Robot Programming of a Manufacturing Assembly Task Board

March 9, 2024
Author(s)
Medhavi Kamran, Snehesh Shrestha, Arnav Juneja, Shelly Bagchi, Jeremy Marvel, Megan Zimmerman, Vinh Nguyen
Collaborative robot tasks in manufacturing often involve manually placing and recording the robot in various positions throughout the intended task. However, existing methods for programming robot have been shown to cause physical strain and confusion for

FY24 Soft Robotics Report

February 29, 2024
Author(s)
Jennifer Case, Jeremy Marvel
Advances in robotics research have begun incorporating non-traditional materials, such as rubbers and elastomers, into the structure of robots giving them new capabilities. This inclusion of soft materials has highlighted a number of metrology challenges

Augmented Reality Interface for Robot-Sensor Coordinate Registration

August 4, 2023
Author(s)
Vinh Nguyen, Xiaofeng Liu, Jeremy Marvel
Accurate registration of Cartesian coordinate systems is vital to facilitate advanced metrological solutions of industrial robots in production environments. Conducting coordinate registration between industrial robots and their metrological systems

Evaluation of Data-Driven Models in Human-Robot Load-Sharing

September 30, 2022
Author(s)
Vinh Nguyen, Jeremy Marvel
Human-robot load-sharing is a potential application for human-robot collaborative systems in production environments. However, knowledge of the appropriate data-driven models for this application type is limited due to a lack of physical real-world data

Using Full Pose Measurement for Serial Robot Calibration

April 6, 2022
Author(s)
Marek Franaszek, Jeremy Marvel
To ensure smooth robot operations, parameters of its kinematic model and a registration transformation between robot base and world coordinate frame must be determined. Both tasks require data acquired by external sensors that can measure either 3D

Design and Testing of Wireless Motion Gauges for Two Collaborative Robot Arms

March 11, 2022
Author(s)
Yong Sik Kim, Nicholas G. Dagalakis, Jeremy Marvel, Geraldine Cheok
Most existing robot performance evaluation methods focus on single robotic arms performing independent motion tasks. In this paper, a motion gauge is proposed to evaluate the symmetrical coordinated-motion performance between two robotic arms. For this

Improving Automated Insertion Task in Robotics by Reducing Registration Error

April 2, 2021
Author(s)
Geraldine S. Cheok, Marek Franaszek, Karl Van Wyk, Jeremy Marvel
A peg-in-hole operation is representative of common tasks performed in assembly lines by robots. It requires registration of the coordinate frame where a part resides to the robot frame. Poor registration causes misalignment of the peg and the hole which

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

February 8, 2021
Author(s)
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
Author(s)
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
Author(s)
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

Human-Supervised Semi-Autonomous Mobile Manipulators for Safely and Efficiently Executing Machine Tending Tasks

October 16, 2020
Author(s)
Sarah Al-Hussaini, Shantanu Thakar, Hyojeong Kim, Pradeep Rajendran, Brual C. Shah, Alec Kanyuck, Jeremy Marvel, Satyandra K. Gupta
Mobile manipulators can be used for machine tending and material handling tasks in small volume manufacturing applications. These applications usually have semi-structured work environment. The use of a fully autonomous mobile manipulator for such

Improving 3D Vision-Robot Registration for Assembly Tasks

April 3, 2020
Author(s)
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

Helping Robots Stay on Target

December 2, 2019
Author(s)
Elena R. Messina, Jeremy Marvel
For decades, many manufacturers have counted on robots to tirelessly produce parts of predictable quality. One of the key attributes of robots is their repeatability, which means that their tool tip will return to the same pre-programmed location with a

Reducing Localization Error of Vision-Guided Industrial Robots

June 18, 2019
Author(s)
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