3D UAV Landing Path Planning Across Altitude Layers
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Solution Overview
Problem
Current path planning technologies for aerial vehicles (AVs) are complex, time-consuming, and insufficiently automated, particularly for unmanned aerial vehicles (UAVs), as they fail to efficiently generate valid routes that avoid obstacles and restricted areas, leading to limitations in return-to-home (RTH) and return-to-landing (RTL) features, which often require high computational resources and may result in unsafe or impossible flight paths.
Innovation Solution
A method and system that generate a pseudo-optimal 3D path by identifying constraints at different altitude layers, computing a lateral path to circumvent common constraints, and then projecting this path vertically to create a conflict-free route, reducing computational demands and improving reliability, allowing for autonomous re-routing around obstacles and restricted zones.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If existing RTL solutions use a straight path from current position to home, then the path generation is simple, but the safety is compromised as it may fly over populated areas, restricted airspace, and no-flying zones
Solution Approach 1:
The patent transitions from 2D horizontal path planning to 3D vertical path planning by introducing altitude layers. The system divides the airspace into multiple altitude layers and computes paths in three dimensions, allowing the AV to climb above or descend below obstacles and restricted areas that would block a straight horizontal path, thereby maintaining safety while avoiding the limitations of simple 2D routing.
Solution Approach 2:
The patent segments the vertical airspace into multiple discrete altitude layers. Each layer is processed separately to identify constraints and compute valid paths. This segmentation allows the system to handle complex 3D navigation by breaking it down into manageable 2D horizontal planes at different altitudes, then combining them into a complete 3D path.
2Reliability
If pre-defined conflict-free RTH path is used at the time of modeling, then the path avoids obstacles and restricted areas, but the AV may run out of fuel or batteries when trying to land
Solution Approach 1:
The patent implements dynamic path recomputation during flight rather than relying on a static pre-defined path. The system continuously monitors the AV's position, remaining energy, and environmental constraints, then dynamically generates optimized RTL paths that account for current battery levels and changing conditions, allowing flexible adjustment between safety and energy conservation.
Solution Approach 2:
The patent changes the parameter of path optimization from static obstacle avoidance to dynamic multi-criteria optimization that includes remaining energy levels. The system adjusts path parameters such as altitude, distance, and waypoints based on real-time battery status, selecting paths that balance safety requirements with energy conservation to ensure successful landing.
3Adaptability or versatility
If flexible RTH or RTL is implemented to bring the AV back to a safe point, then the adaptability is improved, but high computational resources are required
Solution Approach 1:
The patent segments the complex 3D path planning problem into simpler 2D sub-problems by processing each altitude layer separately. This decomposition reduces the computational complexity from solving a single complex 3D optimization problem to solving multiple simpler 2D problems, making flexible RTL achievable with reduced computational resources while maintaining adaptability.
Solution Approach 2:
By introducing the vertical dimension with multiple altitude layers, the patent transforms intractable 2D path planning problems into more manageable 3D problems where vertical separation provides additional degrees of freedom. This dimensional expansion allows the system to find valid paths around horizontal obstacles more efficiently, reducing the computational burden compared to attempting complex 2D avoidance maneuvers.
Data Source
AI summary
A system and a method for generating a 3D path from a source to a destination for an aerial vehicle is disclosed. An example system includes a managing unit to select a group of altitude layers including source and destination and generate a 2D horizontal scenario by identifying constraints to avoid at each altitude layer. The example system includes a path computing unit to determine common constraints for the altitude layers of the 2D horizontal scenario and compute a 2D lateral path avoiding the common constraints. The managing unit generates a 2D vertical scenario based on a projection of the previously computed 2D lateral path onto the constraints at the altitude layers. The path computing unit computes a 2D vertical path avoiding constraints of the 2D vertical scenario. The managing unit composes 3D waypoints of a conflict-free 3D path according to the 2D lateral path and 2D vertical path.