Networked Drone Swarm Payload Lift With In-Flight Drone Replacement
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Solution Overview
Problem
Drones used for package delivery face limitations in cargo weight capacity, flight duration, and reliability due to lift capability constraints, leading to low efficiency and reliability in single-drone systems.
Innovation Solution
A networked drone system comprising multiple drones that work together to support a shared payload, using magnetic or mechanical attachment systems and inertial measurement units for stability control, allowing for increased capacity and redundancy, enabling in-flight drone replacement and efficient horizontal flight.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single drone is used for package delivery, then the system is simple and cost-effective, but the cargo weight capacity is limited due to lift capability constraints
Solution Approach 1:
The delivery system is segmented into multiple independent drones that can operate individually or collectively. Each drone maintains its own lift capability while the swarm collectively handles heavier payloads, resolving the contradiction between system simplicity and cargo capacity through modular division.
Solution Approach 2:
Multiple drones are merged into a coordinated swarm system that functions as a unified delivery platform. The combined lift capability of multiple drones enables heavy cargo delivery while maintaining individual drone simplicity, effectively combining the advantages of both approaches.
2Ease of manufacture
If a single drone is used for package delivery, then the operational cost is low, but the flight duration and distance are limited
Solution Approach 1:
The drone swarm enables continuous delivery operations through coordinated flight patterns and relay capabilities. Drones can maintain prolonged mission duration by working in sequence or simultaneously, ensuring continuous useful action without requiring individual drones to have extended battery life.
Solution Approach 2:
The swarm system dynamically adjusts flight configurations, task分配, and coordination strategies based on mission requirements. This dynamic adaptability allows the system to optimize for either cost efficiency or extended range/duration depending on the specific delivery scenario.
3Ease of operation
If a single drone is used for package delivery, then the system is simple to operate, but the reliability is low due to single point of failure
Solution Approach 1:
Each drone in the swarm maintains independent operational capabilities and redundancy. The failure of one drone does not compromise the entire system, as other drones can compensate for the loss. This local quality assurance through distributed architecture maintains reliability while preserving operational simplicity.
Solution Approach 2:
The swarm system incorporates built-in redundancy where multiple drones are positioned to provide backup capabilities. This beforehand cushioning ensures that if one drone fails, the system has pre-positioned resources to maintain mission continuity, thereby improving reliability without significantly increasing operational complexity.
4Weight of moving object
If multiple drones are used to increase cargo capacity, then the cargo carrying capacity is improved, but the system complexity increases
Solution Approach 1:
Each drone in the swarm is designed as a universal platform capable of performing multiple functions: independent delivery, coordinated lifting, relay operations, and mutual support. This multi-functionality reduces the need for specialized components and simplifies the overall system architecture while maintaining high cargo capacity.
Solution Approach 2:
The system dynamically changes operational parameters such as drone formation, lift distribution, and coordination protocols based on cargo weight and delivery requirements. This parameter adaptability allows the swarm to scale from simple to complex configurations as needed, managing system complexity while maximizing cargo capacity.
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
The networked drone system enhances cargo carrying capacity and extends delivery range while maintaining stability and reliability, reducing the risk of failure and improving safety by allowing for in-flight drone replacement and precise control.
Implementation Method 1
an electrically reversible magnet configured to connect the support platform to one or more of the plurality of drones
Implementation Method 2
The electrically reversible magnet includes at least a pair of opposite polarity magnets in a substantially planar alignment
Data Source
AI summary
The disclosure generally provides methods, systems and apparatus for networked drone systems. In an exemplary networked drone system, a plurality of smaller drones are attached to a fixed platform to increase delivery payload, distance, reliability and safety. As a drone nears charge depletion, it is replaced in-flight with a new drone. Thus, the networked drone system need not be grounded to replace the depleted drone. In another embodiment, flight efficiency is increased by providing collapsible wins to the networked drone system.