Preview Access a sample playlist of videos here: https://www.youtube.com/watch?v=_wOgNZWWoEE&list=PLrP4k_0quIDOl6A6J49_GtRlZbLaV964v&index=1 Description This dataset contains 84 video recordings of a robotic head and neck mounted on a UR3 manipulator performing controlled neck movements. The dataset was developed to investigate the relationship between neck kinematics and the visual information generated by robot motion during human–robot interaction. The recordings capture three fundamental neck motion types corresponding to the primary rotational degrees of freedom of the human cervical spine: Roll (lateral head tilt) Pitch (head nodding) Yaw (head shaking) Each motion is performed under systematically varied kinematic parameters, enabling quantitative analysis of how movement amplitude, acceleration, and repetition influence the visual salience and information content of robotic neck behaviour. Dataset Composition The dataset consists of videos generated from combinations of: Parameter Values Motion axis Roll, Pitch, Yaw Angular displacement 5°, 10° Acceleration 0.5, 2.0 m/s² Repetition frequency 1, 2, 3 repetitions All videos were recorded using a fixed camera positioned in front of the robotic head under consistent experimental conditions. There are two versions of the dataset available: a compressed (207MB) and a non-compressed (3.52 GB) dataset. File Naming Convention Each video file follows the format: (motion_axis)_(angle)_(acceleration)_(frequency).mp4 Examples: roll_10_2.0_3.mp4 pitch_5_0.5_1.mp4 yaw_10_0.5_2.mp4 where: motion_axis ∈ {roll, pitch, yaw} angle ∈ {5, 10} degrees acceleration ∈ {0.5, 2.0} m/s² frequency ∈ {1, 2, 3} For example, the file roll_10_2.0_3.mp4 contains a roll motion with a maximum angular displacement of 10°, executed with an acceleration of 2.0 m/s² and repeated three times. Visual Information Analysis The dataset was designed to support the measurement of visual information generated by robot neck movements. However it can also be used for surveys and determining future robotic designs as well. Applications Potential applications of the dataset include: Human–robot interaction research Analysis of expressive robotic motion Embodied information and communication studies Motion perception and visual salience modelling Robot behaviour generation and evaluation Benchmarking information-theoretic measures of robot movement Citation If you use this dataset in your research, please cite the associated publication describing the embodied information framework and visual entropy analysis methodology. This will be acceptance upon the acceptance of the publication that carries more information regarding the dataset.