Learning to Control an Android Robot Head for Facial Animation

TL;DR

This paper presents a novel method for controlling an Android robot head to generate facial expressions by using 3D landmarks, improving the mapping from human expressions to robotic ones, with positive survey feedback.

Contribution

It introduces a new approach using 3D landmarks for better facial expression mapping on robot heads, extending prior work to a different robot model.

Findings

Participants preferred the new landmark-based mapping in surveys.

The approach shows promise but requires further refinement.

Improved expression control over previous methods.

Abstract

The ability to display rich facial expressions is crucial for human-like robotic heads. While manually defining such expressions is intricate, there already exist approaches to automatically learn them. In this work one such approach is applied to evaluate and control a robot head different from the one in the original study. To improve the mapping of facial expressions from human actors onto a robot head, it is proposed to use 3D landmarks and their pairwise distances as input to the learning algorithm instead of the previously used facial action units. Participants of an online survey preferred mappings from our proposed approach in most cases, though there are still further improvements required.