UAV Fleet Control with Multi-Channel Links and GNSS Correction
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Solution Overview
Problem
Fleet operations of unmanned aerial vehicles (UAVs) face challenges in communication stability, navigation precision, task assignment efficiency, and signal synchronization due to interference, location errors, and labor-intensive initial arrangements, leading to potential control loss and increased collision risks.
Innovation Solution
A fleet operation system with a ground control device that employs multiple communication channels with different radio wave characteristics, satellite correction signals, and emergency control mechanisms to ensure stable communication, precise navigation, efficient task assignment, and redundancy in signal transmission, allowing for real-time corrections and emergency operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If one communication method or frequency channel is used for fleet operation, then the communication system is simple, but communication is interrupted and stability is poor
Solution Approach 1:
The communication system is segmented into multiple independent communication channels (first communication channel, second communication channel, third communication channel) that operate simultaneously. Each channel can transmit different types of signals (control signals, video signals, telemetry data), allowing the system to maintain communication stability even if one channel experiences interference or failure.
Solution Approach 2:
The communication system is designed with multi-functionality by enabling a single communication platform to handle multiple types of signals and protocols across different channels. The system can dynamically allocate channels based on task requirements, making it adaptable to various communication needs while maintaining overall system simplicity through unified management.
2Measurement precision
If GNSS location information is used for navigation, then the navigation system is simple, but location error is large (3m to 5m) increasing collision risk
Solution Approach 1:
The navigation system merges multiple location determination methods by combining GNSS with visual odometry, inertial measurement unit (IMU) data, and relative positioning algorithms. This integration allows the system to achieve high-precision location accuracy (reducing error from 3-5m to sub-meter level) by cross-validating and fusing data from multiple sources, while maintaining system manageability through centralized processing.
Solution Approach 2:
Visual markers and artificial landmarks are introduced as intermediary elements to enhance location precision. These markers serve as reference points that bridge the gap between coarse GNSS positioning and fine relative positioning, enabling the UAV fleet to achieve meter-level or sub-meter-level accuracy without requiring complex autonomous navigation algorithms.
3Productivity
If tasks are assigned in the order of UAV IDs with constant formation, then task assignment is simple, but a lot of labor is required and it is inefficient
Solution Approach 1:
The task assignment system transitions from a static ID-based allocation method to a dynamic formation-aware assignment mechanism. The system dynamically adjusts task distribution based on real-time UAV positions, formation configurations, and task requirements. This allows automated optimization of task assignment without requiring manual intervention or fixed formation patterns, significantly improving efficiency while maintaining computational simplicity.
4Reliability
If one synchronization signal is transmitted to multiple UAVs, then the signal transmission is simple, but packets may be delayed or lost reducing synchronization reliability
Solution Approach 1:
The synchronization signal transmission implements local quality differentiation by assigning different transmission characteristics to different signal components. Critical synchronization packets are transmitted with higher priority and redundancy across multiple channels, while less critical data uses standard transmission protocols. This selective enhancement of signal quality where needed improves synchronization reliability without requiring complete system-wide complexity increases.
Data Source
AI summary
A fleet operation system for an unmanned aerial vehicle (UAV) is provided. The UAV according to an embodiment of the present disclosure includes a plurality of UAVs configured to fly in a fleet according to a determined task plan; and a ground control device for a fleet operation of the plurality of UAVs. The ground control device includes a first communication unit configured to receive flight information comprising a locations from the plurality of UAVs and transmit the task plan and satellite correction information to each of the plurality of UAVs; a second communication unit configured to transmit the satellite correction information to each of the plurality of UAVs; and a central processing unit configured to generate and transmit the task plan of each of the plurality of UAVs to each of the plurality of UAVs through the first communication unit.