UAV Co-Travel Routing to Extend Range via Ground Vehicles
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Solution Overview
Problem
Unmanned aerial vehicles (UAVs) face limitations in range due to battery or fuel constraints, leading to potential delays or failures in reaching destinations, especially over longer distances.
Innovation Solution
A method where a network entity directs UAVs to co-travel with other vehicles, such as trucks or buses, by analyzing route information and transmitting instructions for efficient energy and time savings, allowing the UAVs to land and hitch a ride, thereby extending their range and reducing travel time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If the UAV flies directly to the destination using its own power, then it maintains independence and direct control, but it consumes excessive battery/fuel and cannot reach distant destinations
Solution Approach 1:
The patent introduces ground vehicles as intermediary carriers that the UAV can board to travel long distances. The UAV flies to a ground vehicle, boards it to reach distant locations, then flies to the final destination. This mediator system extends the UAV's effective range without requiring larger batteries.
Solution Approach 2:
The journey is segmented into multiple phases: flight to ground vehicle, ground transport, then flight to destination. This segmentation allows the UAV to use different transportation modes optimally - aerial for short hops and ground transport for long distances, thereby conserving energy.
2Loss of time
If the UAV travels long distances directly, then it maintains direct routing, but the travel time becomes excessively long
Solution Approach 1:
Ground vehicles serve as time-efficient mediators for long-distance transport. The system calculates optimal routes that combine UAV flight and ground vehicle travel to minimize total travel time, leveraging the speed advantages of both transportation modes.
Solution Approach 2:
The routing system dynamically adjusts the journey composition based on real-time conditions, selecting the optimal mix of flight and ground transport segments to minimize both time and energy consumption while adapting to changing environmental factors.
3Reliability
If the UAV uses larger batteries to extend range, then it increases autonomy, but the device complexity and weight increase
Solution Approach 1:
Instead of increasing battery capacity, the system uses ground vehicles as external energy carriers. This approach extends range capability without modifying the UAV's power system, avoiding increased weight and complexity while maintaining reliability.
4Object-affected harmful factors
If the UAV flies directly to distant destinations, then it maintains direct path efficiency, but environmental impact increases due to longer flight duration
Solution Approach 1:
Ground vehicles act as low-emission mediators for long-distance transport segments. By replacing prolonged UAV flight with ground-based transport, the system reduces overall carbon footprint and environmental impact while maintaining or improving delivery speed.
Data Source
AI summary
A method (20) performed in a network entity (4, 11, 12) is provided for directing an unmanned aerial vehicle (2) to a destination. The method (20) comprises obtaining (21) route information for at least a first vehicle (3a, 3b) and for the unmanned aerial vehicle (2), establishing (22), based on the route information, that a criterion for co-traveling with the first vehicle (3a, 3b) is fulfilled, and transmitting (23), to the unmanned vehicle (2), information enabling the unmanned aerial vehicle (2) to co-travel with the first vehicle (3a, 3b). Methods in an unmanned aerial vehicle and in a network entity, and an unmanned aerial vehicle, network entity, computer programs and computer program products are also provided.