The ability to keep gaze concentrated on a point of interest during
continuous bipedal locomotion (when the body might pitch, yaw or roll
in response to uneven terrain) is an automatic function that humans
perform rather efficiently. Modeling the fundamental sensorimotor
strategies associated with head and body control during walking and
turning has led to understanding a basic human function. It is
expected to be the basis for designing bipedal robots that can
maneuver more efficiently over uneven terrain, which makes up the bulk
of the solid surface of the earth.
Such terrain is extremely challenging for the robots --- wheeled robots and cumbersome many-legged robots --- that have been most widely used by robotics researchers. Such robots are popular because they are statically stable in motion, and so the thorny problems of balance and dynamic stability can be avoided. However, the next generation of robot vehicles will have to operate in conditions that will require gaits that involve dynamic stability. As a result, robotics researchers are starting to take dynamically stable motion seriously.
The purpose of the proposed work is to develop a state-of-the-art Bipedal Robot Facility for doing research on making robots walk in a dynamically stable, and thus more human, fashion. The overall goal of this research project is to develop computational tools and techniques to support the automatic design of auction mechanisms using approaches from machine-learning and evolutionary computation.
(Taken from the project proposal...)
More specific information about the work carried out on the project may eb found in the papers on the publications page.