3D Scene Representation for Robotic Manipulation
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Solution Overview
Problem
Existing robotic manipulators have limited perception of their surroundings, making it difficult to navigate and interact with environments effectively for tasks like obstacle avoidance and object manipulation.
Innovation Solution
A system that uses multi-view RGB images to generate a three-dimensional representation of a scene, integrating dense 3D reconstruction, primitive shape estimation, and full 6-DoF pose estimation of known objects, leveraging COLMAP, CasMVSNet, and a multi-view extension of the DOPE method for improved scene understanding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If multi-view RGB images are used to generate 3D representation, then scene understanding capability is improved, but system complexity increases
Solution Approach 1:
The system segments the complex task of scene understanding into three distinct modules: (1) dense 3D reconstruction module that generates point clouds from multi-view images, (2) primitive shape estimation module that identifies geometric shapes from point clouds, and (3) pose estimation module that determines 6-DoF poses of objects. This segmentation allows each module to specialize in a specific aspect of scene understanding while maintaining manageable complexity.
Solution Approach 2:
The patent introduces intermediate representations to bridge different processing stages: point clouds serve as intermediaries between 2D images and 3D scene understanding, primitive shape estimates act as intermediaries between raw point clouds and final object poses. These intermediaries simplify the overall processing pipeline by breaking down complex transformations into manageable steps.
2Measurement precision
If dense 3D reconstruction is performed, then obstacle avoidance accuracy is improved, but computational time increases
Solution Approach 1:
The system performs preliminary dense 3D reconstruction of the static environment background before robotic manipulation tasks. This pre-computed 3D representation serves as a foundation for subsequent operations, allowing the system to avoid repeating computationally intensive reconstruction during time-critical manipulation tasks. The preliminary 3D model enables faster real-time updates and obstacle avoidance decisions.
Data Source
AI summary
One or more images (e.g., images taken from one or more cameras) may be received, where each of the one or more images may depict a two-dimensional (2D) view of a three-dimensional (3D) scene. Additionally, the one or more images may be utilized to determine a three-dimensional (3D) representation of a scene. This representation may help an entity navigate an environment represented by the 3D scene.