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Robotics Advanced Research Alliance – Universities and Corporations

Advanced Robotic Research Alliance between Universities and Corporations have been going on for years and now AUBO Robotics’ AUBO-i5 collaborative robot arm is the technology behind exciting new research that’s due to be presented at ICRA 2018 (21-25 May 2018; Brisbane, Australia). The project –which incorporates machine learning, teleoperation, and human-robot collaboration– demonstrates what happens when you combine AUBO Robotics’ commitment to building symbiotic alliances among researchers and research institutions with robotics specialists exploring advanced ideas about human-robot collaboration.

Advanced Robotic Research Alliance between Universities and Corporations have been going on for years and now AUBO Robotics’ AUBO-i5 collaborative robot arm is the technology behind exciting new research that’s due to be presented at ICRA 2018 (21-25 May 2018; Brisbane, Australia). Held annually, ICRA is the premiere global event for robotics researchers.

The project –which incorporates machine learning, teleoperation, and human-robot collaboration– demonstrates what happens when you combine AUBO Robotics’ commitment to building symbiotic alliances among researchers and research institutions with robotics specialists exploring advanced ideas about human-robot collaboration.

Team lead, Dr. Cong Wang, an assistant professor in the New Jersey Institute of Technology, took some time recently to speak with AUBO Robotics about his research, why the AUBO-i5 was chosen for the project and the key factors that make the AUBO-i5 a “wonderful research robot.”

Researcher On A Mission
Dr. Cong Wang is a researcher on a mission to help bring about a state of “ubiquitous coexistence” between humans and robots.

Inspired in part by the many science fiction movies that show robots and humans casually sharing public and private spaces, Wang’s experiments push the boundaries of human-robot interaction and test the limits of current robot capabilities.

In 2017, Wang’s team built a bionic hand and motion capture glove designed to teach a robot by demonstration. They then combined this technology with a machine learning system that enabled the robot to learn much like a human would –through practice and self-evaluation.

The robot was able to learn how to flip a nunchuck –a neat trick that involves making a nunchuck spin around the back of your hand and catching it again– in a matter of hours.

Most importantly, the system developed by Wang and his colleagues is non-task-specific. This means that robots could be trained to perform a wide variety of complex, dynamic motor skills that are beyond traditional robot systems.

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