Terrain Traverse Optimization for Multi-Constraint Rover Routing
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Solution Overview
Problem
Current route planning for vehicles and rovers, such as those on Mars, is a labor-intensive, manual process that struggles to optimize multiple constraints simultaneously, often resulting in functional compromises due to the complexity of terrain analysis and the need for frequent replanning.
Innovation Solution
The Traverse Optimizing Planner (TOP) employs a multivariate stochastic optimization algorithm using 3D terrain data to generate optimized routes that can be quickly adjusted, incorporating constraints like shortest distance, smoothest terrain, and least altitude change, allowing for real-time adaptations and Pareto-optimal solutions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If manual route planning is used for terrain analysis, then route planning can be performed with simple tools, but the process becomes labor-intensive and time-consuming
Solution Approach 1:
The patent replaces manual mechanical route planning with an automated computer-based system that uses algorithms to analyze terrain data and generate optimized routes, eliminating the labor-intensive manual process while maintaining simplicity through software automation
Solution Approach 2:
The system enables self-service route planning where the computer automatically performs terrain analysis and route optimization without requiring manual intervention, allowing the process to serve itself through automated computation
2Device complexity
If manual route planning is used, then the process can be simple, but it struggles to optimize multiple constraints simultaneously
Solution Approach 1:
The patent implements a universal optimization algorithm that can handle multiple constraints simultaneously (distance, terrain smoothness, altitude change, vehicle capabilities) within a single integrated system, making the process versatile while maintaining computational efficiency
Solution Approach 2:
The system optimizes routes by dynamically adjusting multiple parameters including distance, terrain roughness, altitude changes, and vehicle-specific constraints, allowing simultaneous optimization of diverse factors through parameter-based control
3Reliability
If frequent replanning is performed to adapt to terrain changes, then route optimization can be maintained, but the complexity of terrain analysis increases
Solution Approach 1:
The patent implements a feedback mechanism where the system continuously monitors terrain data and vehicle position, automatically replanning routes when deviations or new obstacles are detected, maintaining optimization through iterative refinement rather than complex repeated analysis
Solution Approach 2:
The system performs preliminary terrain analysis and identifies potential challenges in advance, allowing proactive route adjustments before problems arise, reducing the need for complex reactive replanning
Data Source
AI summary
Various examples are provided for object identification and tracking, traverse-optimization and/or trajectory optimization. In one example, a method includes determining a terrain map including at least one associated terrain type; and determining a recommended traverse along the terrain map based upon at least one defined constraint associated with the at least one associated terrain type. In another example, a method includes determining a transformation operator corresponding to a reference frame based upon at least one fiducial marker in a captured image comprising a tracked object; converting the captured image to a standardized image based upon the transformation operator, the standardized image corresponding to the reference frame; and determining a current position of the tracked object from the standardized image.