3D UAV Inspection Route Segmentation Under Flight Constraints
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Solution Overview
Problem
Efficiently inspecting large-scale industrial asset infrastructure, such as powerlines and pipelines, using small UAVs is logistically challenging due to coordination of crews, UAV endurance, radio communication constraints, governmental regulations, terrain, and weather conditions.
Innovation Solution
A computing system is configured to receive asset, UAV, and regulation information to determine a 3-D global asset-inspection plan, segmenting the inspection into UAV flight segments defined by launch locations, optimizing routes to reduce costs and constraints like no-fly zones while maintaining communication and battery capacity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If a single continuous UAV flight path is used to inspect extensive asset infrastructure, then inspection coverage is maximized, but UAV battery capacity and communication range constraints prevent completion of the entire route
Solution Approach 1:
The patent divides the continuous inspection route into multiple discrete flight segments, each within the UAV's battery and communication range capabilities. The system identifies optimal segmentation points along the asset infrastructure and assigns intermediate launch locations, allowing the inspection to be completed in sequential segments while maintaining full coverage of the extensive infrastructure.
2Area of stationary object
If multiple crews are coordinated to inspect long distances, then inspection coverage increases, but operational complexity and coordination requirements increase significantly
Solution Approach 1:
The system employs autonomous UAVs that execute pre-planned flight segments independently without requiring human crew coordination during operation. The computing system automatically generates optimized flight plans, selects launch locations, and sequences segments, eliminating the need for multiple human crews and their associated coordination complexities while maintaining comprehensive inspection coverage.
3Productivity
If UAV flight routes are extended to cover more assets, then inspection efficiency improves, but radio communication constraints and regulatory no-fly zones become limiting factors
Solution Approach 1:
The system dynamically adjusts flight routes and launch locations based on real-time constraints including no-fly zones, communication range limitations, and terrain features. The computing system processes regulatory information and environmental data to generate adaptive flight plans that optimize inspection efficiency while automatically routing around restricted areas and maintaining communication connectivity throughout each segment.
4Measurement precision
If comprehensive asset inspection is performed, then data quality improves, but travel distance and time consumption increase
Solution Approach 1:
The system performs preliminary route optimization and launch location selection before execution, pre-calculating the most efficient segmented paths that minimize travel distance while ensuring comprehensive asset coverage. By planning segments in advance with optimized sequencing and positioning, the system reduces unnecessary flight time and positioning maneuvers while maintaining high-quality inspection data collection throughout the route.
Data Source
AI summary
A computing system obtains asset information, unmanned aerial vehicle (UAV) information, and regulation information, and determines, based on the obtained information, a 3-D global asset-inspection plan including a plurality of UAV route segments and respective UAV launch locations.