Cleaning Robot Trajectory Video Tracking Dataset
#Video Tracking #Trajectory Prediction #Target Detection #Intelligent Cleaning Devices #Robot Route Control #Machine Vision
- 500 records
- 1.6G
- MP4
- CC-BY-NC-SA 4.0
MOBIUSI INC
Updated:2026-02-04
AI Analysis & Value Prop
With the widespread use of intelligent cleaning devices, cleaning robots have become an important part of modern home and office environments. However, current cleaning technology still faces many challenges in route planning and obstacle avoidance in complex environments. Existing solutions, such as laser or ultrasonic-based navigation systems, have certain limitations in accuracy and real-time performance. This dataset aims to enhance the autonomous navigation and dynamic environment adaptability of robots through video tracking technology. Data collection was carried out using high-definition cameras in various complex household and commercial environments, covering different lighting conditions and floor materials. The data has undergone multiple rounds of expert annotation to ensure high precision and consistency in trajectory and obstacle annotations. The annotation team is composed of computer vision and robotics experts, with a team size of over 20 people. Preprocessing steps include video stabilization, frame extraction, data augmentation, and more. The data is organized by scene and complexity for easy retrieval and use.
Dataset Insights
Sample Examples
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| duration | string | Duration |
| quality | string | Resolution |
| track_points | int | The number of marked points in the video indicating the cleaning robot's trajectory. |
| environment_type | string | The type of environment where the cleaning robot is operating, such as home, office, or mall. |
| robot_speed | float | The speed of the cleaning robot in the video, measured in meters per second. |
| obstacle_count | int | The number of obstacles in the video that interfere with the cleaning robot's path. |
| track_precision | float | The precision of the recorded trajectory of the cleaning robot, typically represented in meters as a measure of error. |
| light_conditions | string | The lighting conditions during video recording, such as bright or dim. |
| robot_battery_level | float | The percentage of remaining battery power of the cleaning robot at the time of video recording. |
| robot_orientation | string | The initial orientation of the cleaning robot in the video, such as North, South, East, or West. |
| cleaning_coverage | float | The percentage of the area cleaned by the robot in the video relative to the total area. |
| noise_level | float | The noise level of the cleaning robot while operating in the video, measured in decibels. |
Compliance Statement
| Authorization Type | CC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike) |
| Commercial Use | Requires exclusive subscription or authorization contract (monthly or per-invocation charging) |
| Privacy and Anonymization | No PII, no real company names, simulated scenarios follow industry standards |
| Compliance System | Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs |
Frequently Asked Questions
- What are the main application areas of this dataset?
- The dataset is primarily used in the field of smart devices, particularly for research in intelligent navigation and planning.
- How is the video data in this dataset collected?
- The video data is collected by tracking the movement paths of cleaning robots in various environments.
- What types of research can this dataset support?
- The dataset supports various research types, including intelligent navigation, path planning, and environment recognition.
- Why is this dataset useful for intelligent navigation research?
- It is useful because it provides real-world trajectory data of cleaning robots, which is crucial for developing and testing intelligent navigation algorithms.
- Can this dataset be used for machine learning model training?
- Yes, the trajectory videos in this dataset are very suitable for training and optimizing machine learning models.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2026,
title={Cleaning Robot Trajectory Video Tracking Dataset},
author={MOBIUSI INC},
year={2026},
url={https://www.mobiusi.com/datasets/ce6fdb2ff1daf55d57e02b4f476ddebb},
urldate={2026-02-04},
keywords={Cleaning Robot Dataset, Video Tracking Data, Intelligent Device Trajectory Analysis},
version={1.0}
}Using this in research? Please cite us.
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