3D Work Zone Control Using Point Cloud Tool Tracking
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Solution Overview
Problem
Existing process control systems for work tasks on objects in 3D work zones face challenges such as the need for complex marker systems, limited ability to recognize different workpieces, and difficulties in automatically detecting new workpieces or maintaining accuracy when parts of the object are occluded.
Innovation Solution
The use of LIDAR or TOF sensors to capture a 3D point cloud of the scene, allowing for the recognition and identification of objects without external markers, and enabling the determination of the position and orientation of both tools and objects in real-time, even when parts of the object are occluded.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex marker systems are used to detect tool position and orientation, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent extracts and removes the complex marker system from the detection setup. Instead of using markers on tools and objects, the system uses a camera to capture images of the tool and object directly, extracting only the necessary visual information for position and orientation detection without the overhead of marker systems.
Solution Approach 2:
The patent replaces the mechanical marker system with an optical imaging system. A camera captures images of the tool and object, and image processing algorithms determine positions and orientations from these images, substituting the mechanical marker-based approach with an optical field-based approach.
2Measurement precision
If traditional optical systems are used to detect object position, then ease of operation is maintained, but measurement precision deteriorates when parts of the object are occluded
Solution Approach 1:
The patent transitions from 2D image coordinates to 3D spatial coordinates through coordinate transformation. The system captures 2D images from a camera, then transforms these into 3D position and orientation data by establishing correspondence between image coordinates and real-world coordinates, enabling accurate spatial measurement even when parts are occluded.
Solution Approach 2:
The patent creates a universal detection system that can handle both visible and occluded parts of objects. By using feature point detection and coordinate transformation, the system can determine the position and orientation of the entire object or tool even when only partial features are visible in the image.
3Productivity
If manual work task monitoring is used, then ease of operation is maintained, but productivity decreases
Solution Approach 1:
The patent implements self-service automation where the system automatically captures images, detects feature points, determines positions and orientations, and monitors work tasks without human intervention. The camera system and image processing algorithms work autonomously to provide real-time work task monitoring, eliminating the need for manual observation.
Solution Approach 2:
The patent establishes a feedback loop where the camera continuously captures images of the work area, the system processes these images to detect tool and object positions, and this information is fed back to monitor and control work task execution. This closed-loop feedback enables automatic productivity monitoring and process control.
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
This approach provides a more robust and flexible process control system capable of accurately identifying and tracking multiple objects and tools in real-time, reducing the need for complex marker systems and improving system reliability and accuracy.
Implementation Method 1
LIDAR or TOF sensors to capture a 3D point cloud of the scene
Implementation Method 2
LIDAR or TOF sensors to capture a 3D point cloud of the scene
Data Source
AI summary
A method for process control of work tasks by a tool on an object includes optically determining the position and orientation of the tool over time, for which purpose a marker attached to the tool is captured in an image. The position and orientation of the object is optically determined over time using a sensor that optically captures a scene with the object and tool, each pixel being associated with distance information in the form of a 3D point cloud, and the position and orientation of the object being determined from the pixels and the distance information. It is determined over time, by comparison, when the tool is in a defined 3D work zone, in which case a working position of the tool is signaled, and execution of a work task is enabled, parameterized and/or recorded by a process control system.