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Datasets:
webxos
/
wavebender_dataset_v2

Tasks:
Robotics
Reinforcement Learning
Tabular Regression
Modalities:
Tabular
Text
Formats:
json
Size:
< 1K
Tags:
drone
slam
physics
art
telemetry
obstacle-avoidance
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pandas
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License:
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xet
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1
wavebender_dataset_v2
File size: 2,904 Bytes 
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---
license: mit
task_categories:
- robotics
- reinforcement-learning
- tabular-regression
tags:
- drone
- slam
- physics
- art
- telemetry
- obstacle-avoidance
- synthetic
- robotics
---

[![Website](https://img.shields.io/badge/webXOS.netlify.app-Explore_Apps-00d4aa?style=for-the-badge&logo=netlify&logoColor=white)](https://webxos.netlify.app)
[![GitHub](https://img.shields.io/badge/GitHub-webxos/webxos-181717?style=for-the-badge&logo=github&logoColor=white)](https://github.com/webxos/webxos)
[![Hugging Face](https://img.shields.io/badge/Hugging_Face-🤗_webxos-FFD21E?style=for-the-badge&logo=huggingface&logoColor=white)](https://huggingface.co/webxos)
[![Follow on X](https://img.shields.io/badge/Follow_@webxos-1DA1F2?style=for-the-badge&logo=x&logoColor=white)](https://x.com/webxos)

<div style="
    background: #00FF00;
    border-left: 4px solid #00FF00;
    padding: 1.5rem;
    margin: 2rem 0;
    font-family: 'Fira Code', 'Courier New', monospace;
    color: #00FF00;
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">
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 _    _    __  _  _  ____  ____  ____  _  _  ____  ____  ____ 
( \/\/ )  /__\( \/ )( ___)(  _ \( ___)( \( )(  _ \( ___)(  _ \
 )    (  /(__)\\  /  )__)  ) _ < )__)  )  (  )(_) ))__)  )   /
(__/\__)(__)(__)\/  (____)(____/(____)(_)\_)(____/(____)(_)\_)

</div>
  
# V2

*UNDER DEVELOPMENT*

*This dataset was generated using the WAVEBENDER app by webXOS* 

LINK: https://huggingface.co/datasets/webxos/wavebender_dataset/tree/main/generator
(Download this app to create your own similar datasets)

Generated synthetic dataset for drone autonomy ML training, including telemetry signals 
(acceleration, gyro, altitude, velocity, battery, GPS), SLAM (obstacle detection/mapping), 
and avoidance maneuvers in simulated 3D environments with configurable parameters (complexity, 
noise, frequency, dynamic obstacles). Synthetic drone datasets are generally used to overcome 
real-world data limitations for unmanned aerial vehicles (UAVs).

## Key Features

- Realistic 3D simulated environments
- Configurable parameters: scene complexity, sensor noise, update frequency, dynamic/moving obstacles
- Multi-modal data: raw telemetry + processed SLAM + maneuver labels

## Included Signals

- **Telemetry**  
  - Acceleration (3-axis)  
  - Gyroscope (3-axis)  
  - Altitude (barometric / fusion)  
  - Velocity vector  
  - Battery level / voltage  
  - GPS position & velocity  

- **SLAM / Perception**  
  - Obstacle detection & mapping output  
  - Distance to nearest obstacles  

- **Labels / Actions**  
  - Avoidance maneuver executed (direction, type, intensity)

## Status

Under active development — v2 expands variety, realism, and annotation quality over v1 (link below)
https://huggingface.co/datasets/webxos/wavebender_dataset