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Commercial
Robotic Household Activities Dataset
This droid dataset includes recordings of cleaning, laundry folding, dishwashing activities, combining head-mounted video with detailed robotic data streams from seven 9-axis IMU units placed on the chest, upper arms, forearms, wrists. The robot dataset captures data from 3-axis accelerometers, 3-axis gyroscope, and 3-axis magnetometer sensors, using onboard sensor-fusion to generate orientation quaternions for motion tracking and robotic learning.
-
- Hours
- 1,000
- Computer Vision
- Machine Learning
- Human Activity Recognition
- Robot Learning
- Motion Analysis
- Computer Vision
- Machine Learning
- Human Activity Recognition
- Robot Learning
- Motion Analysis
This droid dataset includes recordings of cleaning, laundry folding, dishwashing activities, combining head-mounted video with detailed robotic data streams from seven 9-axis IMU units placed on the chest, upper arms, forearms, wrists. The robot dataset captures data from 3-axis accelerometers, 3-axis gyroscope, and 3-axis magnetometer sensors, using onboard sensor-fusion to generate orientation quaternions for motion tracking and robotic learning.
- Computer Vision
- Machine Learning
- Human Activity Recognition
- Robot Learning
- Motion Analysis
-
- Hours
- 1,000
Dataset Info
| Characteristic | Data |
| Description | 1,000 hours of multimodal recordings of cleaning, laundry folding, and dishwashing activities |
| Data types | Video (head-mounted), 9-axis IMU streams |
| Tasks | Human Activity Recognition, Motion Analysis, Multimodal Learning, Action Segmentation |
| Hours of recordings | 1,000 |
| IMU placements | Chest, Upper arms, Forearms, Wrists |
| Sensor outputs | 3-axis accelerometer, 3-axis gyroscope, 3-axis magnetometer, Orientation quaternions |
| Labeling | Metadata (counter, duration, task, date, video size, sensor size, recording version) |
Technical
Characteristics
| Characteristic | Data |
| Video extension | MP4 |
| Video source | Head-mounted camera |
| Extension of labeling file | JSON |
| IMU specification | 7 units, 9-axis each |
| IMU data types | Linear acceleration, Angular velocity, Magnetic field orientation |
| Orientation format | Quaternions (from onboard sensor-fusion) |
Dataset Use Cases
FAQs
What is included in this robotic dataset?
The dataset includes 1,000 hours of multimodal recordings featuring cleaning, laundry folding, and dishwashing tasks. It consists of head-mounted video and synchronized sensor data streams collected from real humans performing household activities.
What types of annotations are provided in the dataset?
Annotations include structured metadata such as task type, recording duration, timestamps, recording version, and sensor file sizes. These labels enable precise alignment between video, sensor data, and manipulation tasks for model training.
Can I request a sample of the dataset before purchasing or downloading it?
Yes. Unidata provides free samples so you can evaluate the video quality, sensor data structure, and labeling format. This allows researchers to assess whether the robotic data supports their robotic systems and learning methods before full access.
What are the sources of data for Unidata robotic datasets?
This robot activities dataset was collected by a verified partner of Unidata. Data collection followed controlled protocols to ensure consistent, high-quality robot and human demonstration recordings.
What sensor data does the dataset contain?
The dataset contains data from seven 9-axis IMU units placed on the chest, upper arms, forearms, and wrists. Each IMU provides linear acceleration, angular velocity, magnetic field orientation, and orientation quaternions generated through onboard sensor fusion.
What makes this dataset different from standard activity recognition datasets?
Unlike traditional activity datasets that rely only on video or wearable sensors, this robot dataset combines synchronized first-person video, seven 9-axis IMU streams, orientation quaternions, and structured metadata. This rich multimodal data makes it particularly valuable for robot learning, human activity recognition, motion analysis, and next-generation Physical AI applications.
How are Unidata datasets licensed?
Unidata follows a dual-licensing model. Free samples are available for testing and evaluation, while full robotic datasets are provided exclusively through purchase.
Do Unidata datasets comply with GDPR and data privacy regulations?
Yes. All datasets are curated in compliance with GDPR and applicable data protection laws. Data is collected from legally permissible sources to ensure ethical use in robotics and machine learning research.
How are Unidata datasets stored and managed?
Unidata stores all datasets securely on AWS cloud infrastructure with compliance to ISO 27001 and ISO 27701 standards. This ensures high availability, scalability, and secure handling of robotic data and sensor streams.
How long does it take to receive the dataset after purchase?
Once you submit a request, Unidata will contact you to confirm requirements and complete documentation. After signing and payment, the dataset is delivered within 3–10 days.
Still have questions about using Unidata datasets?
Read our user-guides
Unidata Cases
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