UAV Ride-on Route Planning for Battery-Limited Delivery Range
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Solution Overview
Problem
Unmanned aerial vehicles (UAVs) have limited battery capacity, restricting their flight distance and preventing them from completing one-way or round-trip long delivery routes.
Innovation Solution
Determine candidate riding vehicles along an autonomous flight route, calculate a riding flight route based on vehicle locations and speeds, and control the UAV to ride these vehicles to extend its flight range.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the unmanned aerial vehicle flies relying on its own power along the autonomous flight route, then the flight route can be completed autonomously, but the battery capacity is exhausted before reaching the destination due to limited battery capacity
Solution Approach 1:
The patent introduces ground vehicles as intermediary carriers to assist the UAV in long-distance delivery. The UAV transfers packages to ground vehicles at transfer points along the route, and later retrieves them near the destination. This mediator system enables the UAV to complete long delivery routes without depleting its limited battery capacity, resolving the contradiction between route completion reliability and energy consumption.
2Length of moving object
If the unmanned aerial vehicle uses ground vehicles for assistance, then the delivery distance is extended, but the system complexity increases due to coordination between multiple vehicles
Solution Approach 1:
The system performs preliminary actions by pre-calculating and planning the entire multi-vehicle route in advance, including identifying transfer points and coordinating ground vehicle schedules before the UAV departs. This advance planning reduces real-time coordination complexity while enabling extended delivery distances through seamless UAV-ground vehicle transitions.
Solution Approach 2:
The system implements feedback mechanisms where the UAV and ground vehicles continuously communicate their positions, statuses, and arrival times. This real-time feedback enables dynamic route adjustments and ensures smooth transfers between UAV and ground vehicles, managing system complexity through automated coordination while extending delivery range.
Data Source
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AI summary
An unmanned aerial vehicle riding route processing method, apparatus and device, and a readable storage medium, the method includes: determining candidate ride vehicles according to an autonomous flight route of an unmanned aerial vehicle from a flight start point to a flight destination (S101); determining a riding flight route of the unmanned aerial vehicle according to current locations of the candidate ride vehicles (S102); and controlling the unmanned aerial vehicle to ride at least one of the candidate ride vehicles to travel from the flight start point to the flight end point according to the riding flight route (S103). The unmanned aerial vehicle rides at least one vehicle when traveling from the flight start point to the flight end point, thus greatly reducing a distance that the unmanned aerial vehicle flies relying on its own power, thereby saving power consumption of the unmanned aerial vehicle and extending a delivery distance of the unmanned aerial vehicle.