Drifting perceptual patterns suggest prediction errors fusion rather than hypothesis selection: replicating the rubber-hand illusion on a robot

TL;DR

This study demonstrates that both humans and robots experience perceptual drift due to prediction error fusion during body illusion experiments, challenging the hypothesis selection view.

Contribution

It replicates the rubber hand illusion in a robotic system and proposes a unified model of body inference based on prediction error minimization.

Findings

Similar drift patterns in humans and robots

Perceptual drift driven by prediction error fusion

Supports unified predictive coding and causal inference model

Abstract

Humans can experience fake body parts as theirs just by simple visuo-tactile synchronous stimulation. This body-illusion is accompanied by a drift in the perception of the real limb towards the fake limb, suggesting an update of body estimation resulting from stimulation. This work compares body limb drifting patterns of human participants, in a rubber hand illusion experiment, with the end-effector estimation displacement of a multisensory robotic arm enabled with predictive processing perception. Results show similar drifting patterns in both human and robot experiments, and they also suggest that the perceptual drift is due to prediction error fusion, rather than hypothesis selection. We present body inference through prediction error minimization as one single process that unites predictive coding and causal inference and that it is responsible for the effects in perception when we are subjected to intermodal sensory perturbations.