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Robotic systems continue to grow as essential tools in strengthening U.S. manufacturing competitiveness by enabling dramatically greater responsiveness and
Artificial intelligence (AI) in the form of advanced machine learning models has been widely adopted in the technology world today. These machine learning
Recent advancements in robotic arms and end-effectors have the potential to accelerate the use of robotics for assembly. The force sensing and compliance
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
Joseph A. Falco, Daniel Hemphill, Kenneth E. Kimble, Elena R. Messina, Adam Norton, Rafael F. Ropelato, Holly A. Yanco
This paper describes a set of metrics and supporting benchmarking protocols for determining the performance characteristics of robot end-effectors. In the short