Timely Negotiation and Correction of Shared Intentions With Body Motion
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Current robot architectures for modeling interaction behavior are not well suited to the dual task of sequencing discrete actions and incorporating information instantly. Additionally, for communication based on body motion, actions also serve as cues for negotiating interaction alternatives and to enable timely interventions. The paper presents a dynamical system based on the stable heteroclinic channel network, which provides a rich set of parameters to isntantly modulate motions, while maintaining a compact state graph abstraction suitable for reasoning, planning and inference.
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