Multi-UAV Mission Planning With Autonomous Recharging Stations
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Solution Overview
Problem
Current autonomous navigation systems for UAVs are limited in their ability to perform complex multi-drone operations continuously, lack support for intelligent coordination, continuous 24/7 operations, automatic precise landing, and automatic recharging, and are not designed to control air and ground-capable robots dynamically and reliably.
Innovation Solution
A system that simultaneously controls and coordinates multiple UAVs using a planning system that includes navigational and scheduling algorithms, allowing for dynamic mission planning, energy management, and adaptation to uncertainties, with the ability to refuel and reposition UAVs autonomously, using software-directed deterministic planning and AI interfaces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a single operator remotely pilots each UAV individually, then each UAV can be controlled with simple systems, but the system cannot perform complex multi-drone operations continuously and lacks intelligent coordination capability
Solution Approach 1:
The control system is segmented into a central planning system that handles high-level coordination and individual UAV controllers that execute specific commands. This segmentation allows complex multi-drone operations to be coordinated intelligently while each individual UAV maintains relatively simple control hardware and software.
Solution Approach 2:
A central planning system acts as an intermediary between the operator and multiple UAVs. This mediator receives mission objectives, generates coordinated flight plans for multiple drones, and distributes commands appropriately, enabling intelligent coordination without requiring each UAV to have complex autonomous decision-making capabilities.
2Duration of action of stationary object
If UAVs operate with limited battery life, then the system structure can be simplified, but continuous 24/7 operations cannot be achieved
Solution Approach 1:
The system performs preliminary actions by pre-planning mission sequences that include automatic recharging stops. The planning system calculates optimal recharging intervals and schedules, ensuring UAVs return to base for battery replacement before depletion, thereby enabling continuous 24/7 operations without requiring complex real-time battery management during flight.
Solution Approach 2:
The system maintains continuity of useful action through automatic recharging cycles. While one UAV is recharging, another can continue mission operations, ensuring the overall system maintains continuous operational capability. The planning system coordinates these cycles to minimize interruption to mission objectives.
3Measurement precision
If manual landing procedures are used, then the landing system can be simple, but automatic precise landing and recharging cannot be achieved
Solution Approach 1:
The UAV system performs self-service through automatic precise landing and autonomous recharging. Upon return to base, the UAV automatically aligns and lands on the docking station using onboard sensors and guidance systems. The docking station then automatically connects power and replaces batteries, eliminating the need for manual intervention and achieving high precision landing and recharging.
4Adaptability or versatility
If basic navigation systems are used, then the system can be simpler, but dynamic mission planning and adaptation to uncertainties cannot be achieved
Solution Approach 1:
The planning system implements dynamics by generating flexible mission plans that can adapt to changing conditions. The system continuously monitors UAV positions, battery levels, and mission progress, dynamically adjusting flight paths and recharging schedules in real-time to optimize mission completion while accounting for uncertainties and changing environmental conditions.
Data Source
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AI summary
An automated system and method for controlling a plurality of unmanned aerial vehicles (UAVs) is described. The system can include a receiver, a transmitter, and at least one processor in communication with a memory. The receiver receives first telemetric data from the plurality of UAVs. The transmitter is configured to transmit control data to the plurality of UAVs. The memory stores processor-issuable instructions to: substantially simultaneously determine a plurality of plans for each of the plurality of UAVs and for a predetermined time period based at least on the first telemetric data; and iteratively revise the plurality of plans.