Terrain Trafficability Assessment for Autonomous Rover Navigation
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Solution Overview
Problem
Current rover navigation algorithms primarily rely on detecting and avoiding geometric hazards, lacking effective methods to assess and adapt to terrain-induced hazards that pose mobility challenges due to wheel-terrain interaction properties, which can lead to unpredictable slip and potential vehicle immobilization in unknown or changing terrains.
Innovation Solution
The implementation of a terrain trafficability assessment method using image data to determine terrain classes, select slip prediction models, estimate slope, predict slip amounts, and apply heuristic mappings to provide trafficability levels, with the ability to adjust mappings based on actual slip measurements and update models dynamically to improve route planning and navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If terrain classification techniques are used for route planning, then the rover can identify safe or unsafe terrain, but the system lacks the ability to accurately predict wheel-terrain interaction and slip behavior
Solution Approach 1:
The system implements feedback by continuously monitoring actual slip measurements from wheel encoders and inertial measurement units, comparing them against predicted slip values, and using the difference to update the terramechanics model parameters in real-time, improving prediction accuracy throughout the mission
Solution Approach 2:
The system changes parameters by dynamically adjusting terramechanics model parameters (such as soil shear strength, wheel sinkage, and slip ratios) based on real-time slip measurements and terrain conditions, allowing the model to adapt to unknown or changing terrains
2Adaptability or versatility
If the rover traverses unknown terrain without accurate slip prediction, then exploration capability is maintained, but the risk of vehicle immobilization increases
Solution Approach 1:
The system applies dynamics by making the terramechanics model adaptive and dynamic rather than static, allowing model parameters to change in real-time based on actual terrain conditions and slip measurements, enabling the rover to adapt to unknown terrains while maintaining mobility reliability
Solution Approach 2:
The system performs preliminary action by using the terramechanics model to predict slip and trafficability before the rover actually traverses a terrain region, allowing proactive route planning and avoidance of potentially immobilizing terrain
3Measurement precision
If real-time slip prediction and model updating are implemented, then trafficability assessment accuracy improves, but computational complexity and processing requirements increase
Solution Approach 1:
The system applies local quality by focusing computational resources on predicting and updating parameters specifically related to wheel-terrain interaction (slip, sinkage, shear strength) rather than analyzing all possible terrain properties, maintaining precision while managing complexity
Data Source
AI summary
A rover or semi-autonomous or autonomous vehicle may use an image classifier to determine a terrain class of regions of an image of the terrain ahead of the rover or vehicle. The regions of the images are used to estimate the slope of the terrain for the different regions. The terrain class and slope are used to predict an amount of slip the rover will experience when traversing the terrain of the different regions. A heuristic mapping for the terrain class may be applied to the predicted slip amount to determine a hazard level for the rover or vehicle traversing the terrain.