Autonomous UAV Formation Navigation for Dynamic Flight Path Coordination
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Solution Overview
Problem
The operation of multiple aerial vehicles in synchronized formations is inefficient and complex due to nonsynchronous flight paths, which can make missions less efficient, more complicated, and dangerous, especially in hazardous environments where traditional manned vehicles are not suitable.
Innovation Solution
An autonomous aerial vehicle navigation system that allows aerial vehicles to communicate and adjust flight paths based on sensor data, enabling them to dynamically change formations and navigate through challenging environments while maintaining safety and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple aerial vehicles operate in synchronized formations with autonomous control, then mission efficiency and safety are improved, but system complexity and coordination requirements increase
Solution Approach 1:
The patent combines multiple aerial vehicles into a unified formation control system where vehicles operate as a coordinated unit. The formation management module integrates individual vehicle control with group coordination, allowing synchronized operations while sharing computational and sensing resources across the fleet, thereby improving mission efficiency without proportionally increasing overall system complexity.
Solution Approach 2:
The autonomous formation flight system is segmented into distinct functional modules: navigation module, formation management module, obstacle detection module, and communication module. This segmentation allows each module to be developed, tested, and optimized independently, reducing the complexity burden of the overall system while enabling efficient coordinated operations through modular integration.
2Adaptability or versatility
If aerial vehicles dynamically adjust formations based on sensor data, then adaptability to environmental conditions is improved, but real-time communication and coordination requirements increase
Solution Approach 1:
The formation configuration is made dynamic rather than static. The formation management module continuously receives sensor data from individual vehicles and environmental sensors, then automatically adjusts formation parameters such as spacing, orientation, and velocity in real-time. This dynamic adaptability allows the fleet to respond to changing environmental conditions without requiring complex manual coordination.
Solution Approach 2:
The system implements continuous feedback loops where sensor data from each vehicle and the environment is processed by the formation management module, which then generates updated control commands. This feedback mechanism enables automatic adaptation to environmental conditions while distributing the computational burden across the fleet, reducing the complexity of centralized communication requirements.
3Reliability
If autonomous control is implemented for aerial vehicles in hazardous environments, then risk to personnel is reduced, but reliability requirements for control logic and communication increase
Solution Approach 1:
The aerial vehicles are equipped with autonomous navigation and obstacle avoidance capabilities that allow them to operate independently in hazardous environments without human intervention. The navigation module processes sensor data and generates control commands autonomously, while the formation management module coordinates vehicle interactions. This self-service capability removes personnel from dangerous situations while the distributed autonomous control architecture reduces the complexity burden of centralized safety-critical systems.
Data Source
AI summary
In one example, a method of operating a plurality of aerial vehicles in an environment includes receiving, at a first command module of a first aerial vehicle navigating along a first flight path, sensor data from one or more sensors on board the first aerial vehicle. The sensor data reflects one or more characteristics of the environment. The method further includes determining, via the first command module, a change from a predetermined formation to a different formation for a second aerial vehicle based at least in part on the sensor data, where the predetermined formation and the different formation are relative to the first aerial vehicle. The method also including generating, via the first command module, control signals reflecting the change from the predetermined formation to the different formation and sending the control signals from the first aerial vehicle to the second aerial vehicle.