3D Cliff Detection Mapping for Robot Route Planning
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Solution Overview
Problem
Robots face challenges in navigating around cliffs and ledges, which can result in damage or injury due to the need for rapid detection and response, and existing 3D scanning technologies are resource-intensive and complex.
Innovation Solution
A lightweight processing pipeline using a 3D range sensor and controller to detect cliffs by analyzing vertical differences and slopes, rasterizing points into a map to avoid cliffs, and optimizing navigation around them.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing 3D scanning technologies are used for cliff detection, then detection accuracy is improved, but device complexity and resource consumption increase
Solution Approach 1:
The patent segments the point cloud data into multiple planes (floor plane, cliff plane, object plane) and processes each plane separately. This segmentation allows the system to focus computational resources on detecting vertical drops and slope changes specific to cliffs, rather than processing all points uniformly, thereby maintaining high detection accuracy while reducing overall processing complexity
Solution Approach 2:
The patent extracts only the essential features needed for cliff detection (vertical differences, slope angles, point density) from the full 3D point cloud data. By taking out and focusing on these critical parameters while ignoring redundant information, the system achieves accurate cliff detection with reduced computational overhead and simpler processing pipelines
2Reliability
If comprehensive 3D scanning is performed for environment mapping, then navigation safety is improved, but memory and processor bandwidth consumption increase
Solution Approach 1:
The patent applies partial action by performing 3D scanning and processing only on regions where cliffs are detected or suspected. Instead of continuously processing the entire environment map at full resolution, the system focuses computational effort on critical areas, thereby ensuring navigation safety through comprehensive scanning where needed while conserving processor bandwidth through selective processing
Solution Approach 2:
The patent merges cliff detection functionality with the existing SLAM (Simultaneous Localization and Mapping) pipeline. By combining these functions, the system uses the same sensor data and processing infrastructure for both mapping and cliff detection, eliminating redundant computations and reducing overall processor bandwidth consumption while maintaining navigation safety
3Reliability
If real-time cliff detection is implemented, then response time is improved, but processing speed may be reduced due to complex calculations
Solution Approach 1:
The patent performs preliminary actions by pre-computing and storing the normal vectors for each plane during the initial SLAM mapping phase. When cliff detection is needed, the system uses these pre-computed normals along with simple vertical difference calculations rather than performing full 3D geometric analysis in real-time. This preliminary preparation enables fast real-time detection while maintaining reliability through accurate pre-computed reference data
Data Source
AI summary
Systems and methods for detecting, mapping, and route planning around cliffs for robotic devices are disclosed herein. According to at least one non-limiting exemplary embodiment, a robot processing a three-dimensional range sensor scan may utilize pre-computed neighboring points to detect cliffs, navigable ramps, and holes in a plane of a map used by the robotic device to navigate.