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Search Publications by: Jeremy Marvel (Fed)

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Displaying 26 - 50 of 71

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

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

November 17, 2016
Author(s)
Ariyan M. Kabir, Joshua D. Langsfeld, Shaurya Shriyam, Vinaichandra S. Rachakonda, Cunbo Zhuang, Krishnanand N. Kaipa, Jeremy 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
Author(s)
Krishnanand N. Kaipa, Akshaya S. Kankanhalli-Nagendra, Nithyananda B. Kumbla, Shaurya Shriyam, Srudeep Somnaath Thevendria-Karthic, Jeremy 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
Author(s)
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
Author(s)
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

Addressing Perception Uncertainty Induced Failure Modes in Robotic Bin-Picking

May 3, 2016
Author(s)
Krishnanand N. Kaipa, Akshaya S. Kankanhalli-Nag, Nithyananda B. Kumbla, Shaurya Shriyam, Srudeep Somnaath Thevendria-Karthic, Jeremy Marvel, Satyandra K. Gupta
We present a comprehensive approach to handle perception uncertainty to reduce failure rates in robotic bin-picking. Our focus is on mixed-bins. We identify the main failure modes at various stages of the bin-picking task and present methods to recover

Test Methods for the Evaluation of Manufacturing Mobile Manipulator Safety

April 20, 2016
Author(s)
Jeremy A. Marvel, Roger V. Bostelman
A test methodology for evaluating the safety of mobile manipulators (robot arms mounted on mobile bases) is presented. This methodology addresses the safety concerns relevant to modern, agile manufacturing practices in which mobile manipulators are

Benchmarking Robot Force Control Capabilities: Experimental Results

January 7, 2016
Author(s)
Joseph A. Falco, Jeremy A. Marvel, Richard J. Norcross, Karl Van Wyk
Metrics and test methods are needed to characterize the control capabilities of robots with both intrinsic and extrinsic force sensing. The availability of these benchmarks will motivate research product development, and provide a mechanism for reporting

Adaptive Multi-scale PHM for Robotic Assembly Processes

October 23, 2015
Author(s)
Benjamin Y. Choo, Peter A. Beling, Amy LaViers, Jeremy Marvel, Brian A. Weiss
Adaptive multi-scale prognostics and health management (AM-PHM) is a methodology designed to support PHM in smart manufacturing systems. AM-PHM is characterized by its incorporation of multi-level, hierarchical relationships and PHM information gathered

Linear Temporal Logic (LTL) Based Monitoring of Smart Manufacturing Systems

October 23, 2015
Author(s)
Gerald Heddy, Umer Huzaifa, Peter A. Beling, Yacov Haimes, Jeremy Marvel, Brian A. Weiss, Amy LaViers
The vision of Smart Manufacturing Systems (SMS) includes collaborative robots that can adapt to a range of scenarios. This vision requires a classification of multiple system behaviors, or sequences of movement, that can achieve the same high-level tasks