UGV Path Planning With Adaptive Resolution Obstacle Avoidance
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Solution Overview
Problem
Unmanned ground vehicles (UGVs) face challenges in planning accurate and obstacle-avoiding paths in real-time, especially when navigating areas with unpassable obstacles, as existing methods may delay progression and fail to provide high-resolution obstacle detection efficiently.
Innovation Solution
The method involves generating multiple paths at different angular resolutions, assigning weights based on factors like proximity to obstacles and turning angles, and selecting the path with the lowest weight for real-time navigation, allowing for continuous and efficient obstacle avoidance while updating the path in accordance with sensor data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high angular resolution is used for path planning, then obstacle detection precision is improved, but processing time increases
Solution Approach 1:
The path planning process is divided into multiple iterations where segments are added incrementally. Instead of computing all possible paths at once with high resolution, the system computes paths segment by segment, allowing early termination when a satisfactory path is found, thus reducing overall processing time while maintaining detection precision.
Solution Approach 2:
The angular resolution is dynamically adjusted based on the situation. The system uses a base angular resolution for most segments but increases to a higher angular resolution when segments collide with obstacles, allowing precise obstacle detection only when necessary rather than uniformly across all computations.
2Reliability
If multiple paths are generated and evaluated, then path selection accuracy is improved, but computational complexity increases
Solution Approach 1:
The system generates multiple paths but does not evaluate all possible paths to completion. Instead, it generates a sufficient number of paths with weighted scores and selects from those that meet a threshold, performing partial evaluation rather than exhaustive search, thus reducing computational complexity while maintaining reliable path selection.
Solution Approach 2:
The system uses weighted parameters to evaluate and rank multiple paths efficiently. By assigning weights to different path characteristics (such as distance, obstacle proximity, and turning angles), the system can quickly compare and select the best path without complex computational analysis of all possible route variations.
3Manufacturing precision
If real-time path updating is performed, then navigation accuracy is improved, but processing speed decreases
Solution Approach 1:
The system performs preliminary path planning using available map data before the UGV encounters actual obstacles. This preliminary path is then refined in real-time as sensor data becomes available, allowing the system to maintain high navigation accuracy through continuous updating without requiring complete re-computation of the entire path at full resolution.
Solution Approach 2:
Path updating is performed periodically rather than continuously at full resolution. The system updates the path at regular intervals based on sensor data and progress, performing high-resolution analysis only when necessary rather than constantly, thus maintaining navigation accuracy while preserving processing speed.
Data Source
AI summary
The disclosure relates to real-time autonomous path planning for a vehicle, and to the steering of the vehicle in accordance with the path. The path is planned in accordance with a given map of the area, and the path accuracy depends, inter alia, on the resolution and accuracy of the map.