Coverage Path Layout for Autonomous Vehicle Replenishment Planning
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Solution Overview
Problem
Current navigation planning algorithms for autonomous vehicles in agriculture and construction fail to efficiently generate coverage trajectories that minimize distance and time while accommodating obstacles and the need for replenishment of consumable materials during tasks like fertilizer or seed spraying.
Innovation Solution
A method that uses multivariate optimization to determine optimal track directions and offsets within a work area, incorporating obstacle information and refill station locations to generate traversable trajectories and replenishment paths for autonomous vehicles, ensuring efficient coverage and material replenishment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional navigation planning algorithms are used for autonomous vehicles, then the vehicle can complete basic coverage tasks, but the total distance and time taken to cover the work area is excessive
Solution Approach 1:
The system performs preliminary optimization of track direction and offset before the autonomous vehicle begins coverage. By pre-calculating the optimal track layout that minimizes total distance and turns, the vehicle can execute the predetermined efficient path without real-time decision delays, thereby reducing total coverage time while maintaining high productivity
2Productivity
If traditional navigation planning algorithms are used for autonomous vehicles, then the vehicle can complete basic coverage tasks, but the total distance covered is excessive
Solution Approach 1:
The system optimizes key parameters including track direction angle and offset distance from boundary to minimize total track length. By mathematically determining the optimal combination of these parameters, the system reduces the cumulative distance the vehicle must travel while ensuring complete area coverage, directly improving coverage efficiency
3Ease of operation
If traditional navigation planning algorithms are used for autonomous vehicles, then the vehicle can traverse the work area, but the number of turns is excessive
Solution Approach 1:
The system pre-calculates an optimized track layout that minimizes the number of turns before the vehicle begins operation. By determining the optimal track direction and spacing in advance, the vehicle follows a predetermined path with fewer directional changes, reducing the duration of coverage operations while maintaining ease of traversal
4Productivity
If the autonomous vehicle traverses the work area without optimization, then it can complete coverage, but it cannot timely replenish consumable materials
Solution Approach 1:
The system pre-calculates logistic points along the optimized coverage trajectory where the vehicle should replenish materials. By determining these replenishment locations in advance based on the optimal track layout, the system ensures the vehicle can maintain continuous operation with timely material replenishment, supporting both high productivity and operational reliability
Data Source
AI summary
A method of area coverage planning for an autonomous vehicle includes, at a computer system, receiving information of a boundary of a work area, and laying a plurality of tracks within the boundary of the work area. The plurality of tracks is spaced apart from each other by a spacing. Laying the plurality of tracks includes, based on the information of the boundary of the work area, performing a multivariate optimization to: (i) determine an optimal direction of the plurality of tracks, and (ii) an optimal offset for a first track from the boundary, so as to minimize a total distance of the plurality of tracks. The method further includes generating a trajectory that is traversable by the autonomous vehicle to traverse the plurality of tracks.