presentation we survey a number of force and stiffness sensors developed for surgical robotic systems. These include force and stiffness sensors based on fiber-optic and pneumatic technologies. We explore finite element (FE) modeling of the robot-tissue interface, including inverse FE models for identifying tissue properties for diagnosis. The use of haptic interfaces at the surgeon-master interface is also investigated.

Rong Xiong, Zhejiang University, China
Title: A study on humanoid robots playing table tennis

Abstract: Over the past twenty years, the research on humanoid robots has rapidly advanced, and various humanoid robots have been developed. They can walk, run, dance, play Taiji, etc. The ongoing research on humanoids is moving toward complex task performing in different environments, such as providing domestic service in a home environment or collaborating with human beings to move heavy objects. We take table tennis playing as an entry point to explore related technologies, because both intelligent interaction and dynamic response, which are fundamental factors for future service robots, are required but challenging issues in such a task. We have proposed algorithms for fast visual recognition and accurate trajectory prediction of a Ping-Pong ball and coordinative motion planning and balance maintenance of the humanoid robot, and we have developed a real-time field bus to meet the requirements for quick response. Now the two 165 cm-tall humanoid robots we developed, “Wu” and “Kong,” can play table tennis continuously with each other and with amateur human players. This research topic also provides an interesting point of view for studies on autonomous cooperative or competitive interaction between robots or between a human and a robot. For example, how should the robot learn play motions and play strategies from human players? How should the robot vary its play motion and strategies depending on its real-time perception?

Session 3: Learning and Adaptation in Dynamic Settings

Michael Freed, SRI International
Title: A virtual assistant for e-mail overload

Abstract: E-mail client software is widely used for personal task management, a purpose for which it was not designed and is poorly suited. Past attempts to remedy the problem have focused on adding task management features to the client user interaction. RADAR uses an alternative approach modeled on a trusted human assistant who reads mail, identifies task-relevant message content, and helps manage and execute tasks. This talk describes the integration of diverse AI technologies and presents results from human evaluation studies comparing RADAR user performance to unaided commercial-off-the-shelf tool users and

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