Autonomous Drone Resupply Using GPS Mission Planning
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Solution Overview
Problem
Existing aerial drone technologies require significant human intervention for navigation and product delivery, which may not be practical or desired in certain situations.
Innovation Solution
An unmanned autonomous vehicle system that receives location and product data without human intervention, generates mission data, and navigates to deliver products using a transceiver, GPS, inventory sensors/actuators, and compute devices to autonomously manage drone flight paths and product delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If human intervention is used for drone navigation and product delivery, then control and safety can be maintained, but operational efficiency is reduced and human resources are consumed
Solution Approach 1:
The drone system performs self-navigation, self-monitoring, and self-delivery operations using onboard sensors, processors, and autonomous control algorithms. The system independently tracks its position via GPS, monitors battery levels, navigates to delivery locations, and completes product transfer without human intervention, thereby maximizing productivity while maintaining operational safety through automated protocols
Solution Approach 2:
Manual mechanical control of drone navigation is replaced with electronic autonomous control systems. The mechanical pilot control interface is substituted with automated flight control algorithms, GPS-based navigation, and electronic communication systems that enable the drone to operate independently, eliminating the need for continuous human mechanical intervention
2Productivity
If autonomous navigation is implemented, then operational efficiency increases and human resources are freed, but system complexity increases
Solution Approach 1:
The drone system integrates multiple functions into a single autonomous platform: navigation (GPS and onboard sensors), communication (two-way radio with ground station), monitoring (battery and system status sensors), and delivery (product transfer mechanism). This multi-functional integration achieves high productivity while managing complexity through unified system design rather than separate independent systems
Solution Approach 2:
A ground station serves as an intermediary between the autonomous drone and human operators. The ground station receives telemetry data from the drone, processes navigation information, and can intervene if necessary, thereby reducing the complexity burden on the drone itself while maintaining operational efficiency through automated drone-Ground station communication protocols
3Reliability
If continuous monitoring is performed, then safety and reliability are improved, but energy consumption increases
Solution Approach 1:
The drone implements periodic monitoring cycles rather than continuous monitoring. Sensors check battery levels, position, and system status at predetermined intervals during flight. This periodic approach maintains adequate safety and reliability by detecting issues at regular checkpoints while significantly reducing energy consumption compared to continuous real-time monitoring of all parameters
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables autonomous product delivery without human interaction, reducing errors and allowing individuals to engage in other activities, particularly in scenarios requiring focus like medical care or military operations.
Implementation Method 1
receiving, at a processor, from a global positioning system (GPS) transceiver and without human intervention, location data associated with a target
Data Source
AI summary
A processor-implemented method includes receiving, at a processor, from a transceiver and without human intervention, location data associated with a target. The processor receives, from the transceiver, product data for a resupply request referencing the target, the product data including at least one of a product type or a product quantity. The processor generates, without human intervention, unmanned autonomous vehicle (UAV) mission data based on the location data and the product data, the UAV mission data including a representation of at least one UAV and flight path data for the at least one UAV. The UAV mission data is caused to transmit to at least one UAV controller to cause the at least one UAV controller to initiate navigation of the at least one UAV according to the UAV mission data.