Virtual Fleet Configuration for Scalable Drone Delivery Simulation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Configuring backend systems for simulating fleets of unmanned aerial vehicles (UAVs) is difficult and time-consuming, especially when testing multiple aircraft configurations and software versions, which hinders large-scale simulation of drone delivery operations.
Innovation Solution
A backend automation system is provided that automates the creation and launch of virtual fleets, configures parameters for virtual vehicle binaries, and supports continuous monitoring of fleet performance, enabling efficient simulation of drone delivery operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual configuration methods are used for UAV simulation systems, then configuration accuracy can be ensured, but the time and effort required increases significantly
Solution Approach 1:
The patent uses template-based configuration where pre-defined simulation templates and configuration patterns are copied and adapted for different UAV scenarios. This allows rapid deployment of simulation environments while maintaining consistency and accuracy through proven configurations, eliminating manual setup time for routine simulation scenarios.
Solution Approach 2:
The system automatically adjusts simulation parameters based on input specifications, transforming high-level requirements into detailed configuration settings. This parameter automation handles the complexity of accurate configuration while reducing manual intervention time, as the system dynamically modifies parameters to match desired simulation outcomes.
2Adaptability or versatility
If multiple aircraft configurations and software versions are tested, then simulation comprehensiveness improves, but system complexity increases
Solution Approach 1:
The patent segments the simulation system into modular components, each handling specific aircraft configurations or software versions independently. This modular architecture allows comprehensive testing of multiple configurations without creating a monolithic complex system, as each module can be developed, tested, and managed separately.
Solution Approach 2:
The system implements universal configuration management that handles multiple aircraft types and software versions through a common framework. This multi-functional approach allows the same system infrastructure to support diverse simulation scenarios, reducing overall complexity compared to having separate systems for each configuration.
3Reliability
If virtual fleets are created manually, then configuration control is maintained, but creation speed decreases
Solution Approach 1:
The patent implements pre-configured templates and pre-defined fleet patterns that prepare common simulation configurations in advance. This preliminary action allows rapid fleet creation by simply selecting and instantiating pre-validated configurations, maintaining control through proven templates while dramatically speeding up the creation process.
Solution Approach 2:
The system provides self-service automation where configuration parameters are automatically generated and validated based on high-level specifications. This self-configuration capability maintains reliability through automated validation rules while eliminating manual configuration steps, enabling rapid fleet creation without sacrificing control.
Data Source
AI summary
A method includes receiving configuration data for an unmanned aerial vehicle (UAV) simulation system, the configuration data indicating at least one base location specification, at least one aircraft specification, and at least one virtual vehicle specification and determining an aircraft record comprising, for each of the at least one aircraft to be simulated, aircraft mission data associated with an aircraft identifier of the at least one aircraft to be simulated. The method further includes configuring the UAV simulation system so that each of the at least one aircraft has a corresponding base location as specified by the at least one base location specification and a corresponding vehicle software version as specified by the at least one virtual vehicle specification and executing a simulation of the at least one aircraft carrying out flying missions by using the configured UAV simulation system and updating the aircraft mission data in the aircraft record.