Cognitive and motor compliance in intentional human-robot interaction

TL;DR

This paper explores how intentionality, motor, and cognitive compliance influence human-robot interaction, proposing a variational model and control concepts inspired by neuroscience to understand behavior emergence in humanoid robots.

Contribution

It introduces a novel variational model based on predictive coding and active inference, along with an intermittent control approach for motor compliance in human-robot interaction.

Findings

The model provides insights into intentionality and cognitive compliance.

Experimental results with humanoid robots demonstrate the model's potential.

The approach offers new perspectives for bio-inspired social robotics.

Abstract

Embodiment and subjective experience in human-robot interaction are important aspects to consider when studying both natural cognition and adaptive robotics to human environments. Although several researches have focused on nonverbal communication and collaboration, the study of autonomous physical interaction has obtained less attention. From the perspective of neurorobotics, we investigate the relation between intentionality, motor compliance, cognitive compliance, and behavior emergence. We propose a variational model inspired by the principles of predictive coding and active inference to study intentionality and cognitive compliance, and an intermittent control concept for motor deliberation and compliance based on torque feed-back. Our experiments with the humanoid Torobo portrait interesting perspectives for the bio-inspired study of developmental and social processes.