Online intention recognition for computer-assisted teleoperation

An online intention recognition algorithm for computer-assisted teleoperation is introduced. The algorithm is able to distinguish between phases of a typical object manipulation task. It adopts a new advanced feature extraction algorithm which extracts features from haptic data and uses a Hidden Markov Model for stochastic classification. The method is implemented and validated on a real hardware setup. The obtained results reveal a robust and fast intention recognition.

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