Abstract. We present a model of motor learning based on a combination of Operational Space Control and Optimal Control. Anticipatory processes are used both in the learning of the ...
This paper presents a novel auto-calibration method from unconstrained human body motion. It relies on the underlying biomechanical constraints associated with human bipedal locom...
— Many neural network models of (human) motor learning focus on the acquisition of direct goal-to-action mappings, which results in rather inflexible motor control programs. We ...
Abstract— This paper develops an approach for on-line segmentation of whole body human motion patterns during human motion observation and learning. A Hidden Markov Model is used...
Abstract. Despite the large success of games grounded on movement-based interactions the current state of full body motion capture technologies still prevents the exploitation of p...