3D Feature Point Mapping with Ceiling and Floor Filtering
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Solution Overview
Problem
Existing methods for displaying three-dimensional feature point clouds, such as those used in SLAM for AGVs, often obscure the distinction between features on ceilings and travel surfaces, making it difficult for users to visually recognize obstacles and navigate effectively.
Innovation Solution
An information processing apparatus that acquires a feature point cloud and projects it onto a two-dimensional plane excluding features representing ceilings and travel surfaces, allowing for the display of obstacle boundaries and travel routes with enhanced visibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all feature points including ceiling and floor are displayed on a two-dimensional image, then complete environmental information is provided, but visual recognition of obstacles and travel surfaces becomes difficult
Solution Approach 1:
The patent segments the feature point cloud data by spatial location, separating ceiling features, floor features, and obstacle features. This segmentation allows selective display of only obstacle features on the two-dimensional image, eliminating visual clutter from ceiling and floor points while preserving complete environmental information in the underlying data structure.
Solution Approach 2:
The patent extracts and removes ceiling and floor feature points from the display dataset while maintaining them in the complete environmental model. This extraction process isolates only the obstacle feature points for visualization, solving the contradiction by providing complete information internally while presenting only essential visual elements to the user.
2Ease of operation
If three-dimensional point cloud data is projected onto a two-dimensional plane, then the data can be displayed on a graphical interface, but the distinction between ceiling and travel surface features is lost
Solution Approach 1:
The patent applies local quality by assigning different processing rules to different spatial regions. Ceiling features and floor features are identified by their vertical position and treated differently from obstacle features. This local differentiation allows the system to project data to 2D while preserving the semantic distinction between feature types through selective filtering and labeling.
Solution Approach 2:
The patent uses vertical dimension information (z-coordinate) to differentiate feature types during the 2D projection process. By analyzing the height distribution of feature points, the system can identify ceiling points (high z-values) and floor points (low z-values) and exclude them from obstacle visualization, thereby maintaining feature distinction through dimensional analysis rather than direct visual representation.
Data Source
AI summary
An information processing apparatus includes an acquisition unit configured to acquire a feature point cloud indicating a three-dimensional shape of an environment where a moving object travels, and an output unit configured to output a two-dimensional map indicating positions of feature points on a two-dimensional plane excluding feature points that represent a feature of a ceiling in the environment or a travel surface of the moving object from the feature point cloud.