Aerial Route Planning Using Payload Survivability Estimates
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Solution Overview
Problem
Unmanned aerial drones face challenges in minimizing payload damage and ensuring safety during transit, as they may lose control, leading to potential destruction or harm upon impact, especially with varying environmental conditions.
Innovation Solution
A method and apparatus for generating an aerial navigation route based on a payload survivability estimate, which processes map data to identify features and materials, using real-time and historical data, and sensor data to calculate the probability of the payload remaining functional after impact, thereby optimizing routes to minimize damage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the drone operates over various environments to deliver payloads, then the delivery capability and operational versatility are improved, but the risk of losing control and the probability of payload destruction upon impact increase
Solution Approach 1:
The system performs preliminary analysis of the flight route to identify hazardous areas before the drone begins its mission. Map data is processed in advance to calculate payload survivability estimates for different geographic locations, allowing the routing system to pre-determine safe flight paths that avoid areas where payload loss would be catastrophic.
Solution Approach 2:
The patent introduces an intermediary routing system that acts as a mediator between the delivery objective and the environmental hazards. This system processes map data and survivability estimates to generate optimized routes, effectively shielding the drone operator from directly navigating complex risk environments while still achieving delivery goals.
2Productivity
If the drone flies at high altitude to avoid obstacles, then the operational efficiency is improved, but the payload descent speed increases causing greater impact damage
Solution Approach 1:
The system applies local quality by varying the flight altitude based on the specific characteristics of different geographic areas along the route. Rather than maintaining a constant high altitude for efficiency, the drone adjusts its altitude dynamically - flying higher over safe areas and lower over areas where payload loss would be catastrophic, with these adjustments determined by the processed map data and survivability estimates.
3Loss of time
If the drone takes a direct route to the destination, then the delivery time is reduced, but the exposure to potential hazards increases
Solution Approach 1:
The routing system is dynamic rather than static. It continuously processes map data and survivability estimates to generate optimized routes that balance speed and safety. The system can adapt the route in real-time based on environmental conditions, allowing the drone to maintain high productivity while dynamically adjusting to avoid hazardous areas along the path.
Data Source
AI summary
An approach is provided for calculating a payload survivability estimate and generating aerial routes based on the payload survivability estimate. The approach, for example, involves processing data, such as map data representing the geographic area to identify at least one map feature, at least one material corresponding with the at least one map feature, or a combination thereof. The payload survivability estimate can be based on real-time data, historical data, or a combination thereof. The approach also involves generating a map data layer of a geographic database based on the payload survivability estimate. The approach further involves providing the map data layer as an output.