3D Surface Feature Traversal for Discontinuous Terrain Navigation
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Solution Overview
Problem
Current technologies lack the ability to effectively locate and traverse substantially discontinuous surface features (SDSFs) in heterogeneous topologies, as they fail to integrate multi-criteria models for SDSF identification and trajectory planning with graphing polygons, and do not consider candidate traversal angles and path obstructions.
Innovation Solution
A system that processes point cloud data to filter and segment surfaces, identify SDSFs, create graphing polygons, and determine traversable paths by forming an edge/weight graph, allowing for safe and efficient traversal of SDSFs by autonomous devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional 2D path planning techniques are used, then the system is simple to implement, but it cannot handle 3D terrain and substantially discontinuous surface features
Solution Approach 1:
The patent extends traditional 2D path planning to 3D terrain by incorporating elevation data and creating a multi-dimensional navigation space. The system processes point cloud data to generate 3D surface models and identifies SDSFs in three-dimensional space, enabling autonomous devices to traverse complex terrain that cannot be handled by flat 2D planning algorithms.
Solution Approach 2:
The patent segments the 3D terrain into discrete surface features and graphing polygons. By dividing the complex terrain into manageable segments (SDSFs, drivable surfaces, obstacles), the system can apply specific traversal criteria to each segment independently, making the overall path planning process more tractable while maintaining 3D capability.
2Measurement precision
If multi-criteria models for SDSF identification are implemented, then the accuracy of SDSF detection is improved, but the computational complexity increases
Solution Approach 1:
The patent performs preliminary processing of point cloud data to generate normalized surface models and identify potential SDSFs before applying the full multi-criteria evaluation. By pre-processing the data to remove noise, fill gaps, and organize the point cloud into structured formats, the system reduces the computational burden of subsequent complex analysis while maintaining high identification accuracy.
Solution Approach 2:
The patent applies different processing criteria and levels of analysis to different regions of the terrain. Local area models are created with specific resolutions and feature detection parameters tailored to the characteristics of each region, allowing high-accuracy SDSF identification where needed while reducing processing complexity in less critical areas.
3Manufacturing precision
If graphing polygons are integrated with SDSF trajectories, then the route planning accuracy is improved, but the processing time increases
Solution Approach 1:
The patent pre-generates graphing polygons from the processed point cloud data and stores them as reusable navigation elements. By creating the polygonal representation of the terrain and SDSFs in advance, the system eliminates the need to perform complex geometric computations during real-time path planning, thus maintaining high route planning precision while significantly reducing processing time.
4Reliability
If comprehensive traversal criteria are applied, then the safety of SDSF traversal is improved, but the system responsiveness decreases
Solution Approach 1:
The patent pre-evaluates potential SDSF traversals against comprehensive safety criteria and pre-computes traversal costs and feasibility. By performing this thorough analysis beforehand, the system creates a pre-validated path database that can be quickly queried during operation, ensuring safe traversal decisions without sacrificing real-time responsiveness.
Solution Approach 2:
The patent applies comprehensive traversal criteria selectively based on the situation. For well-characterized SDSFs with known safety profiles, the system may use simplified evaluation, while applying full comprehensive criteria only when uncertainty exists or safety margins are narrow. This selective approach maintains high safety standards while improving overall system responsiveness.
Data Source
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AI summary
Substantially discontinuous surface feature traversal feature of the present teachings can leverage a transport device (TD), for example, but not limited to, an autonomous device or a semi-autonomous device, to navigate in environments that can include features such as substantially discontinuous surface features. The substantially discontinuous surface feature traversal feature can enable the TD to travel on an expanded variety of surfaces. In particular, substantially discontinuous surface features can be accurately identified and labeled so that the TD can automatically maintain the performance of the TD during ingress and egress of the substantially discontinuous surface feature.