Humanoid motion representation by sensory state transitions

Given the complexity and the high number of degrees of freedom humanoid robot motions often are generated off-line, stored in the robot memory and then reproduced. In the simplest cases motor commands are just replayed in open-loop (i.e. feed-forward), in more advanced implementations few parameters are changed on fly to adapt the motion to the external conditions. Indeed, several authors proposed a large variety of techniques to exploit the input from sensory feedback to modify a reference trajectory, in order to cope with environment changes and disturbances. In this paper, we propose a motion representation for humanoid robots that includes the sensory feedback information in the motion representation itself. This motion description allows stabilization against disturbances and environmental changes, but does not require any design or tuning of the relationships between sensory inputs and movement modification. We present experimental results on a simulated small humanoid robot equipped with motor encoders and touch sensors covering the whole body.