Context Orientated Motion Generation: A New Scheme for Humanoid Robot Control

There are two quite different kinds of approaches to the generation of motions for a humanoid robot. The first one optimizes for the robot's pose, i.e. the movement should look similar to human motions (Zordan and Hodgins, 1999), (Dasgupta and Nakamura, 1999), (Riley et al., 2003), (Kuffner et al., 2003), (Erol et al., 2003), and (Ijspeert et al., 2002). The second one attempts to make the robot perform a given task and is thus focused on the accurate movements of the robot's end effectors (Asfour et al., 2000) and (Yigit et al., 2003). In this work, we present a completely new scheme for the motion generation of a humanoid robot called context oriented motion generation. This scheme incorporates the pose oriented approach and the task oriented approach. It is based on a classical trajectory generator and a new context specific motion classifier developed by our group. The trajectory generator creates a set of trajectories and thereby ensures that the given motion task is accomplished by all trajectories. Afterwards, the motion classifier evaluates this set of motions with respect to the given context and selects the optimal trajectory