3D UAV Path Planning for Terrain-Aware Ground Coverage
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Solution Overview
Problem
UAVs face challenges in conserving energy for long-distance flights and efficient ground coverage due to high power requirements, with existing path planning methods not adequately considering terrain and environmental factors like wind effects.
Innovation Solution
A system for optimized path planning that converts two-dimensional geographic coordinates to three-dimensional coordinates using GIS, generating a grid of points for UAVs to cover a predetermined area, incorporating heuristics that account for distance, battery cost, vertical motion, and environmental conditions such as wind effects, to generate efficient flight paths.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If UAVs perform long-distance flights and surveillance tasks, then ground coverage and task completion improve, but energy consumption increases
Solution Approach 1:
The patent transforms the path planning problem from 2D geographic coordinates to 3D space by incorporating elevation data from GIS. This parameter change allows the heuristic algorithm to optimize flight paths considering vertical motion energy costs, terrain-induced drag variations, and altitude-dependent wind effects, thereby reducing overall energy consumption while maintaining ground coverage
Solution Approach 2:
The patent incorporates environmental feedback (wind effects, terrain characteristics) and operational feedback (battery cost, vertical motion energy consumption) into the heuristic path planning algorithm. This feedback mechanism enables dynamic path optimization that adapts to changing conditions, minimizing energy consumption while ensuring complete ground coverage
2Device complexity
If traditional path planning methods are used, then implementation simplicity is maintained, but terrain and environmental factors are not adequately considered
Solution Approach 1:
The patent adds the vertical dimension to traditional 2D path planning by integrating GIS elevation data to create 3D flight paths. This dimensionality change enables the system to account for terrain-induced drag, vertical motion energy costs, and altitude-dependent wind effects, significantly improving terrain adaptability while maintaining algorithmic efficiency through heuristic optimization
Data Source
AI summary
A method includes defining a two-dimensional geographic region by two-dimensional geographic coordinates to define the bounds of the region, converting each of the two-dimensional coordinates to three dimensional coordinates by way of a lookup stored in a computer readable medium, generating a three-dimensional grid of points, each spaced in an arrangement to encompass coverage of a predetermined ground area, and applying heuristics for a shortest path planning, relative to the three-dimensional grid of points.