If we want robots to engage effectively with humans in service applications or in collaborative work scenarios they have be endowed with the capacity to perceive the passage of time and control the timing of their actions. Here we report result of a robotics experiment in which we test a computational model of action timing based on processing principles of neurodynamics. A key assumption is that elapsed time is encoded in the consistent buildup of persistent population activity representing the memory of sensory or motor events. The stored information can be recalled using a ramp-to-threshold dynamics to guide actions in time. For the experiment we adopt an assembly paradigm from our previous work on natural human-robot interactions. The robot first watches a human executing a sequence of assembly steps. Subsequently, it has to execute the steps from memory in the correct order and in synchrony with an external timing signal. We show that the robot is able to efficiently adapt its motor timing and to store this information in memory using the temporal mismatch between the neural processing of the sensory feedback about executed actions and the external cue. ; FCT - Fundació Catalana de Trasplantament(PD/BD/128183/2016)This research was supported by the Marie Curie Network for Initial Training NETT, FCT through the PhD fellowship PD/BD/128183/2016, the FCT-Research Center CMAT (PEstOE/MAT/UI0013/2014), and FCT - Algoritmi research Centre (COMPETE: POCI-01-0145-FEDER-007043 and FCT - Fundação para a Ciência e Tecnologia within the Project ˆ Scope: UID/CEC/00319/2013)
Towards temporal cognition for robots: a neurodynamics approach
2017-01-01
Conference paper
Electronic Resource
English
DDC: | 629 |
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