Autonomous 3D Modeler Capturing Occluded Surfaces
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Solution Overview
Problem
Current 3D scanning techniques face challenges in accurately modeling objects with occluded surfaces, leading to incomplete and inaccurate representations due to the inability to capture complex topology patches and cavities.
Innovation Solution
An autonomous object modeler system that employs a controllable arm with a depth camera and a modeling table, which autonomously changes camera viewpoints and repositions objects to capture occluded surfaces, using algorithms like Power Crust and Cocone to generate complete 3D models, including mass and inertia data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional 3D scanning techniques are used, then the scanning process is simple, but occluded surfaces cannot be captured leading to incomplete models
Solution Approach 1:
The system employs a controllable arm that dynamically repositions the object during scanning, transforming a static scanning setup into a dynamic one. This allows the depth camera to capture occluded surfaces by changing the relative position between camera and object, thereby improving model completeness without requiring multiple fixed cameras.
Solution Approach 2:
A controllable arm acts as an intermediary mechanism between the depth camera and the object. Instead of directly positioning multiple cameras or manually handling the object, the system uses the controllable arm as a mediator to automatically reposition objects, enabling comprehensive surface capture while maintaining system automation.
2Measurement precision
If manual modeling is used, then expert measurement can capture detailed features, but the process is time-intensive
Solution Approach 1:
The system implements self-service automation where the controllable arm autonomously repositions objects based on scanning data without requiring expert intervention. The algorithms automatically identify occluded surfaces and direct the arm to reposition objects accordingly, enabling the system to serve itself and eliminating the need for time-consuming manual expert measurement.
Solution Approach 2:
The patent replaces manual mechanical measurement processes with an automated system combining depth camera sensing, computational algorithms, and controllable arm actuation. This substitution of manual operations with an integrated automated system maintains measurement precision while dramatically increasing productivity.
3Reliability
If signal processing filters are applied, then noise can be smoothed, but occluded surfaces remain unmodeled
Solution Approach 1:
The system performs preliminary actions by proactively repositioning objects during the scanning process before final model generation. Instead of attempting to recover lost information through post-processing filters, the system preemptively captures occluded surfaces by changing object positions, ensuring complete data acquisition before modeling begins.
Data Source
AI summary
An autonomous object modeler includes a modeling table, a controllable arm, a depth camera attached to the controllable arm, and a controller to control operation of the modeling table, the controllable arm, and the depth camera. The modeling table may be movable and includes a mass sensor to produce mass sensor data indicative of a mass of an object positioned on the modeling table. The controllable arm includes a force-torque sensor to produce force-torque sensor data indicative of an inertia of the object while the object is moved by the controllable arm. The controller is configured to control operation of the controllable arm to reposition the object on the modeling table to generate three-dimensional models of the object. The three-dimensional models include the mass data and the inertia data.