Affordance - based altruistic robotic architecture for human - robot collaboration

Abstract

This thesis proposes a computational model for altruistic behavior, shows its im plementation on a physical robot, and presents the results of human-robot interaction experiments conducted with the implemented system. Inspired from the sensorimotor mechanisms of the primate brain, our model utilizes object affordances for both in tention estimation and action execution, in particular to generate altruistic behavior. At the core of the model is the notion that sensorimotor systems developed for move ment generation can be used to process the visual stimuli generated by the actions of the others, and thus can lead to the emergence of altruistic behavior. Therefore, we argue that altruistic behavior is not necessarily a consequence of deliberate cognitive processing but may emerge through basic sensorimotor processes such as error mini mization. In the model, affordances also play a key role by constraining the possible set of actions that an observed actor might be engaged in, enabling an accurate intention inference. The model components are implemented on an anthropomorphic dual-arm manipulator system as functional units to provide the desired functionality. A set of experiments are conducted validating the workings of the components of the model, such as affordance extraction and task execution. Significantly, to asses how human partners interact with our altruistic model deployed robot, extensive experiments with na¨ıve subjects are conducted. Our results indicate that the proposed computational model can explain emergent altruistic behavior in a biologically plausible way, and moreover engage human partners to exploit this behavior when implemented on an anthropomorphic robot.