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Datasets:
A19Lab
/
robot2robotIdentification

Tasks:
Object Detection
Image Classification
Tabular Regression
Modalities:
Tabular
Text
Formats:
json
Languages:
English
Size:
< 1K
Tags:
robotics
uav
ugv
drones
computer-vision
autonomous-systems
Libraries:
Datasets
pandas
License:
Dataset card Data Studio Files
xet
Community
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Robot2RobotIdentification

A dataset for machine-to-machine visual awareness.

Supported by A19Lab, Inc.

Dataset Description

Robot2RobotIdentification is a vision dataset designed to help drones, UGVs, and autonomous robots detect and recognize each other in real-world environments.

As autonomous machines become more common in skies, streets, and industrial spaces, reliable machine-to-machine perception is essential for safety, coordination, and navigation. This dataset supports that need by linking visual annotations with robotic specifications, enabling both recognition and attribute-based understanding.

Note: To respect copyright and minimize size, this repository contains metadata manifests only. The full image dataset is hydrated locally from public video sources using the provided script.

Repository Structure

  • uav_ugv_dataset.json — Visual manifest containing video IDs, timestamps, labels, and bounding box annotations.
  • uav_ugv_specs.csv — Feature database with physical, performance, and sensor attributes for each class.
  • download_dataset.py — Script that downloads source videos and extracts frame-accurate images.

Technical Specifications (uav_ugv_specs.csv)

Every class in this dataset is linked to a detailed Feature Vector stored in uav_ugv_specs.csv.

Category CSV Column Type Description
Identity class_name String Unique directory ID (e.g., dji-mavic-3)
model String Commercial product name
domain String UAV (Aerial) or UGV (Ground)
type String Configuration (e.g., Quadcopter, Tracked, VTOL)
Physical mass_kg Float Total weight including standard batteries
payload_kg Float Maximum additional carrying capacity
length_mm Int Length (Front-to-Back)
width_mm Int Width (Side-to-Side)
height_mm Int Height (Ground-to-Top)
Performance speed_kmh Float Maximum horizontal speed
ascent_speed_kmh Float Vertical rise speed (UAV only)
descent_speed_kmh Float Vertical drop speed (UAV only)
range_km Float Operational distance
endurance_min Int Max flight or drive time in minutes
Features has_tracks Bool TRUE if vehicle uses continuous tracks
has_manipulator Bool TRUE if equipped with a robotic arm/gripper
has_prop_guards Bool TRUE if propellers are enclosed, caged, or ducted
has_thermal Bool TRUE if equipped with thermal camera
has_lidar Bool TRUE if equipped with LiDAR sensor

How to Use

  1. Clone the repository to get the JSON manifests and the Python script.

  2. Install dependencies:

    pip install yt-dlp

Install FFmpeg (required for frame extraction):
https://ffmpeg.org/download.html

  1. Run the downloader: python download_dataset.py
    • This will download the necessary videos from YouTube, extract the specific annotated frames, and organize them into a dataset_raw/ folder.
  2. Load in Python: Use the class_name from the visual annotations to look up the corresponding row in uav_ugv_specs.csv.

Disclaimer & License

License: Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)

Data Source: All data originates from publicly available videos. The dataset repository contains annotations and metadata only. Users must download the actual frames directly from the original video sources using the provided script and comply with all platform terms and copyright rules.

Disclamer

This dataset is published by A19Lab for research, development, and educational purposes only. A19Lab makes no warranties or guarantees regarding the accuracy, completeness, reliability, legality, or fitness for any specific use of the data provided. All data is offered as-is. A19Lab is not responsible for any direct, indirect, incidental, or consequential damages resulting from the use, misuse, or interpretation of this dataset or any derivatives thereof. Users are solely responsible for ensuring their use of the data complies with applicable laws, regulations, platform terms of service, and ethical standards. A19Lab does not endorse or condone any harmful, malicious, or unlawful applications of this dataset.

Support & Contact

Supported by A19Lab, Inc

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