12:00 PM-1:00 PM on October 22, 2014
Location: Marcus Nanotechnology Building 1116
Title: “Computational Modeling and Enhancement of Human Skill”
Abstract:
With the rapidly growing popularity of the Intuitive Surgical da Vinci system, robotic minimally invasive surgery (RMIS) has crossed the threshold from the laboratory to the real world. There are now hundreds of thousands of human-guided robotic surgeries performed every year, and the number is growing rapidly. This is a unique example of the growing paradigm of human-machine collaborative systems—namely systems of machines and computers collaborating with people to perform tasks that neither can perform as effectively alone.
While designed to be an amplifier of human ability, collaborative systems like the da Vinci pose a number of new challenges. In particular, the learning curve is steep and involves mastery of a new and rapidly evolving set of skills and techniques. Yet, at the same time, the availability of easily acquired data also creates new opportunities to create new engineering paradigms for modeling, evaluating, and improving human skill.
In this talk, I will describe our work toward developing effective human-machine collaborative teams. I will spend most of the talk discussing approaches to modeling complex manipulation tasks within in the context of surgery. By creating models for the “Language of Surgery,” I will show that we are able to evaluate the style and efficiency of surgical motion. These models also lead naturally to methods for supporting, or even automating, component actions in surgery as well as in other domains. At the end of the talk, I will briefly touch on our recent work, building on these ideas, to develop collaborative systems for manufacturing.
This talk includes joint work with Sanjeev Khudanpur and Rene Vidal.
Bio:
Gregory D. Hager is a professor and chair of Computer Science at Johns Hopkins University and the deputy director of the NSF Engineering Research Center for Computer Integrated Surgical Systems and Technology. His research interests include collaborative robotics, time-series analysis of image data, image-guided robotics, and medical applications of image analysis and robotics. He is also chair of the Computing Community Consortium and is currently a member of the governing board of the International Federation of Robotics Research. He is a fellow of the IEEE for his contributions to vision-based robotics.
