UAV Point Cloud Flight Planning Around Structures
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current systems for generating flight plans for unmanned aerial vehicles (UAVs) are inadequate in preventing collisions with structures, as they rely on real-time navigation and collision avoidance, which can be dangerous and inefficient, especially when inspecting complex or hazardous areas like nuclear power plants.
Innovation Solution
A system that uses point cloud technology to generate a three-dimensional representation of a geographic area, allowing for the determination of feasible flight plans by simulating potential collisions and assigning buffers to both the UAV and structures to ensure safe navigation, thereby modifying flight plans to avoid collisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If real-time navigation and collision avoidance are used, then the UAV can respond to approaching structures, but the system complexity and safety risks increase
Solution Approach 1:
The patent applies preliminary action by generating a point cloud representation of the environment before the UAV executes the flight plan. This pre-generated spatial model allows the system to simulate and validate the entire flight path in advance, identifying potential collision risks before they occur. The point cloud is created from pre-captured images and processed offline, enabling safety validation without requiring complex real-time navigation systems during actual flight.
Solution Approach 2:
The patent creates a digital copy of the physical environment through point cloud generation. This virtual representation replicates the spatial relationships, structures, and terrain features, allowing the system to simulate flight paths and detect collisions in the digital model before executing them in the real world. This copying approach eliminates the need for complex real-time collision detection systems.
2Manufacturing precision
If waypoints are placed close to structures for detailed inspection, then inspection quality improves, but collision risk increases
Solution Approach 1:
The system performs preliminary validation of the flight plan by simulating the UAV's movement through the point cloud environment before actual execution. During this simulation phase, the system checks whether any waypoint places the UAV too close to structures, considering error buffers for both the point cloud representation and UAV positioning accuracy. This pre-validation allows detailed inspection waypoints to be maintained while eliminating collision risks through advance detection and correction.
Solution Approach 2:
The patent implements beforehand cushioning by introducing error buffers that account for uncertainties in both the point cloud accuracy and UAV positioning. These buffers create a safety margin around structures in the virtual environment, ensuring that even with positioning errors or point cloud inaccuracies, the UAV will not collide with actual structures during flight. This cushioning approach enables close inspection waypoints while maintaining safety.
3Reliability
If point cloud buffers and UAV buffers are added to ensure safety, then collision prevention improves, but the feasible flight space decreases
Solution Approach 1:
The system applies partial action by selectively applying error buffers only in critical areas where collision risk exists, rather than uniformly reducing the entire navigation space. The buffers are dynamically adjusted based on local geometry, structure density, and inspection requirements. This allows the UAV to operate close to structures where safe and necessary for inspection, while maintaining larger safety margins only where needed, thus maximizing feasible flight space while ensuring safety.
Data Source
AI summary
Methods, systems and apparatus, including computer programs encoded on computer storage media for unmanned aerial vehicle flight operations near physical structures or objects. In particular, a point cloud of the physical structure is generated using aerial images of the structure. The point cloud is then referenced to determine a flight path for the UAV to follow around the physical structure, determine whether a planned flight path to desired locations around the structure is possible, determine the fastest route to return home and land from a given position around the physical structure, determine possibility of inflight collision to surface represented in point cloud, or determine an orientation of a fixed or gimbaled camera given a position of the UAV relative the point cloud.