Warehouse Point Cloud Annotation for Real-Time Object Filtering
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Solution Overview
Problem
Current point cloud technologies in warehouse environments face challenges in accurately and efficiently annotating objects, particularly in dynamic settings where objects like pallets and forklifts are frequently moving, and in distinguishing between objects of interest and undesired objects like humans or other moving entities.
Innovation Solution
A system that uses a vehicle equipped with an image capturing device and a space scanning device to generate and annotate point clouds in real-time, allowing for the identification and filtering of objects, enabling the creation of accurate blueprints and improved object tracking without requiring multiple software programs adapted to different environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple software programs are used to annotate point clouds in different warehouse environments, then adaptability to various environments is improved, but device complexity increases
Solution Approach 1:
The patent implements a universal point cloud annotation system that can automatically adapt to different warehouse environments through machine learning models. The system performs multiple functions including object detection, classification, and annotation within a single integrated platform, eliminating the need for multiple specialized software programs while maintaining adaptability across diverse warehouse settings
2Productivity
If real-time annotation is performed on moving objects in dynamic warehouse environments, then productivity is improved, but measurement precision deteriorates due to object movement
Solution Approach 1:
The system performs preliminary actions by capturing and processing point cloud data before objects move significantly. The annotation process is initiated and completed within a short time window to minimize the impact of object movement, ensuring both real-time performance and acceptable precision for dynamic warehouse environments
Solution Approach 2:
The patent implements dynamic tracking mechanisms that adapt to moving objects in real-time. The system continuously updates object positions and adjusts annotation parameters dynamically, allowing accurate tracking and annotation of moving objects without requiring the system to be static or rigid in its approach
3Loss of information
If all objects in the point cloud are annotated, then information completeness is improved, but loss of time increases due to processing overhead
Solution Approach 1:
The system applies local quality by differentiating annotation priorities and detail levels for different object types and locations in the warehouse. Critical objects receive detailed annotation while less important objects receive simplified annotation, reducing overall processing time while maintaining essential information completeness for warehouse operations
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system provides real-time annotation and filtering of point clouds, enabling clear identification and tracking of objects, even in complex warehouse environments, improving accuracy and efficiency in creating blueprints and navigating robotic movements.
Implementation Method 1
The space scanning device is configured to measure distances to the objects and generate optical scan data (e.g., point cloud data) usable to generate a point cloud of the room
Data Source
AI summary
A system is provided for automatic identification and annotation of objects in a point cloud in real time. The system can automatically annotate a point cloud that identifies coordinates of objects in three-dimensional space while data is being collected for the point cloud. The system can train models of physical objects based on training data, and apply the models to point clouds that are generated by various point cloud generating devices to annotate the points in the point clouds with object identifiers. The solution of automatically annotated point cloud can be used for various applications, such as blueprints, map navigation, and determination of robotic movement in a warehouse.