Multi-UAV Mission Scheduling With Autonomous Recharging Coordination
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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
An automated system that includes a navigational and scheduling system to simultaneously determine and revise plans for multiple UAVs based on telemetric data, ensuring collision avoidance, battery management, and continuous data acquisition, using a processor and transmitter to coordinate flight and ground navigation, and recharging operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If autonomous navigation systems control multiple UAVs, then operational complexity increases, but system reliability and coordination capability deteriorate
Solution Approach 1:
The system segments the fleet management function into distributed components: each UAV has an onboard flight controller for local navigation decisions, while a central ground control station handles high-level coordination and task allocation. This segmentation allows independent operation of individual UAVs while maintaining reliable fleet-wide coordination through modular communication interfaces.
Solution Approach 2:
The system performs preliminary actions by pre-planning flight paths, task assignments, and coordination protocols before UAV deployment. The ground control station pre-processes mission parameters, generates initial flight plans, and establishes communication protocols, enabling UAVs to autonomously execute coordinated operations without real-time intervention, thus maintaining reliability while scaling to multiple vehicles.
2Duration of action of moving object
If UAVs operate continuously without recharging, then operational duration increases, but energy depletion occurs
Solution Approach 1:
The system implements self-service through automated recharge operations: UAVs autonomously monitor their own battery charge levels, calculate optimal recharge timing and locations, navigate to charging stations, and perform docking procedures without human intervention. This allows continuous fleet operation as UAVs independently manage their energy consumption and recharge cycles.
Solution Approach 2:
The system uses feedback mechanisms where UAVs continuously transmit battery status data to the ground control station, which monitors energy levels and dynamically adjusts mission parameters. When charge levels fall below thresholds, the system automatically recalculates flight plans to include recharge stops, ensuring continuous operation while preventing energy depletion through real-time monitoring and adaptive planning.
3Area of stationary object
If multiple UAVs operate in the same space, then mission coverage increases, but collision risk increases
Solution Approach 1:
The system applies asymmetry in spatial coordination by assigning UAVs asymmetric roles and trajectories within the mission area. Instead of symmetric patrol patterns, the ground control station generates differentiated flight paths where each UAV operates in semi-exclusive zones or follows staggered temporal schedules in shared zones. This asymmetric coordination reduces collision probability while maintaining comprehensive area coverage through complementary surveillance patterns.
Data Source
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.