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README.md

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----
-license: apache-2.0
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+---
+title: "Fall Prediction Dataset for Humanoid Robots"
+datasets:
+- naos-fall-prediction
+tags:
+- humanoid-robotics
+- fall-prediction
+- machine-learning
+- sensor-data
+- robotics
+- temporal-convolutional-networks
+license: 
+- apache-2.0
+---
+
+# Fall Prediction Dataset for Humanoid Robots
+
+## Dataset Summary
+This dataset consists of **37.9 hours of real-world sensor data** collected from **20 Nao humanoid robots** over the course of one year in various test environments, including RoboCup soccer matches. The dataset includes **18.3 hours of walking data**, featuring **2519 falls**. It captures a wide range of activities such as omni-directional walking, collisions, standing up, and falls on various surfaces like artificial turf and carpets.
+
+The dataset is primarily designed to support the development and evaluation of fall prediction algorithms for humanoid robots. It includes data from multiple sensors, such as gyroscopes, accelerometers, and force-sensing resistors (FSR), recorded at a high frequency to track robot movements and falls with precision. 
+
+Using this dataset, the **RePro-TCN model** was developed, which outperforms existing fall prediction methods under real-world conditions. This model leverages **temporal convolutional networks (TCNs)** and incorporates advanced training techniques like **progressive forecasting** and **relaxed loss formulations**.
+
+## Dataset Structure
+- **Duration**: 37.9 hours total, 18.3 hours of walking
+- **Falls**: 2519 falls during walking scenarios
+- **Data Types**: Gyroscope (roll, pitch), accelerometer (x, y, z), body angle, and force-sensing resistors (FSR) per foot.
+
+## Use Cases
+- Humanoid robot fall prediction and prevention
+- Robot control algorithm benchmarking
+- Temporal sequence modeling in robotics
+
+## Licensing
+This dataset is shared under the **apache-2.0** license, allowing use and modification with proper attribution, as long as derivatives are shared alike.
+
+## Citation
+If you use this dataset in your research, please cite it as follows:
+
+---
+license: apache-2.0
+---