I will present in this talk our recent results on human-like motion planning and interaction for training and rehabilitation applications. Our approach for human-like motion planning is based on a multi-modal framework that coordinates locomotion, body positioning, and upper-body action execution. Blending spaces defined from example motions are then introduced for achieving continuous search spaces suitable for planning human-like variations of a given action. Example motions are collected by demonstration by means of a virtual reality interface developed on the UC Merced Powerwall, or by means of a low-cost Kinect-based solution. The overall approach leads to new interfaces for physical therapy applications. Exercises are modeled by demonstration and later autonomously delivered and monitored by virtual therapists. The virtual therapist also functions as an avatar during remote therapy sessions between real therapists and patients. Examples in the context of hand and upper-body motion rehabilitation will be presented.
Biography:
Marcelo Kallmann is founding faculty and associate professor of computer science at the University of California, Merced. Before moving to UC Merced he was research faculty at the computer science department of the University of Southern California (USC) and a scientist at the USC Institute for Creative Technologies (ICT). He obtained his PhD in 2001 from the Swiss Federal Institute of Technology in Lausanne (EPFL). His areas of research include computer animation, virtual reality, motion planning and humanoid robotics. His current interests are related to motion interfaces for virtual reality, planning methods for human-like motions, and path planning in triangulations. In 2012 he is serving as the program co-chair for the 5th International Conference on Motion in Games (MIG). At UC Merced he established and leads the computer graphics research group.
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