Communicative Efficiency of Single vs. Multi-Axis Robot Neck Motion

2026-07-08

AI Summary

This study addresses the information-theoretic efficiency of robotic neck motion in nonverbal communication and investigates how morphological design influences expressive clarity. Building a communication channel model grounded in information theory, the authors systematically manipulated degrees of freedom, amplitude, acceleration, and frequency to generate motion stimuli. Evaluation integrated Shannon entropy of pixel changes, energy consumption measurements, and human perception experiments. The work introduces the “morphological information bottleneck” phenomenon and the “actuator information space” framework, revealing that while a three-degree-of-freedom neck incurs higher energy costs, it conveys less communicative information; conversely, a two-degree-of-freedom configuration achieves peak communicative capacity at 5.26 bits. These findings challenge the conventional assumption that greater anthropomorphic fidelity enhances expressiveness, offering quantitative guidelines for robotic neck design.

Abstract

Nonverbal communication through head and neck movement is fundamental to human social signalling, yet how robotic neck morphology translates motion into communicative information remains poorly understood. We present an information-theoretic framework characterising robot neck movement as a communication channel, quantifying information transmitted and energy expended across varied configurations. Using a robotic neck platform, we recorded 84 video stimuli spanning three rotational degrees of freedom (DoF), varying amplitude, acceleration, and frequency, measuring Shannon entropy of pixel-change signals alongside energy consumption. A perceptual study validated communicative interpretations of each motion. While humans typically engage one axis per gesture, robots are unconstrained by biological architecture, motivating tests up to 3 DoF. Yet communicative information peaks at two DoF and decreases at three despite rising energy cost, a phenomenon we term the morphological information bottleneck. Motion parameter effects were parameter-dependent, some additive, others non-linear. We introduce the Motor Information Space, a framework mapping entropy against energy to expose communicative efficiency across morphologies, in which the optimal configuration achieves 5.26 bits at competitive energy cost. Perception data further confirm multi-axis movements reduce clarity. These findings challenge the assumption that anatomical completeness improves robotic expressiveness, establishing a quantitative basis for morphological design in robots, especially humanoids.

Problem

• communicative efficiency
• robot neck morphology
• nonverbal communication
• information bottleneck
• humanoid robots

Innovation

• information-theoretic framework
• morphological information bottleneck
• Motor Information Space
• robot neck morphology
• communicative efficiency