Modular Vehicle Autonomy Architecture for Rapid Mission Reconfiguration
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Solution Overview
Problem
Existing autonomy systems for vehicles and other systems are limited in extensibility and adaptability, as they are typically designed for narrow mission sets and lack the ability to rapidly adapt to new platforms or domains, making them inflexible and requiring significant redevelopment for different applications.
Innovation Solution
The Adaptable Autonomy Architecture (A3) system, which employs a modular and parameterized software framework that supports generic autonomy algorithms, enabling rapid extension and reconfiguration across various domains and vehicles, including aircraft, ground, sea, and cyber systems, by using a standardized library of parameterized functions and modules.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing autonomy systems are designed for narrow mission sets with specialized algorithms, then they achieve high reliability for specific tasks, but they suffer from poor extensibility and require significant redevelopment for new applications
Solution Approach 1:
The patent implements a universal autonomy system architecture that can perform multiple functions across different domains (aerial, ground, maritime, cyber) through a common framework. The system uses standardized interfaces and parameterized algorithms that can be configured for different vehicle types and mission requirements, eliminating the need for separate specialized systems for each domain.
Solution Approach 2:
The system employs parameterized autonomy algorithms where mission-specific behavior is achieved by changing parameters rather than rewriting code. The architecture allows dynamic adjustment of algorithm parameters to adapt to different vehicle characteristics, environmental conditions, and mission objectives, enabling rapid reconfiguration without structural changes.
2Adaptability or versatility
If autonomy systems are highly specialized for specific vehicle types, then they achieve optimal performance for those vehicles, but they lack adaptability to new platforms
Solution Approach 1:
The autonomy system is divided into modular components with clearly defined interfaces. The architecture separates vehicle-specific parameters from core autonomy algorithms, allowing the system to maintain reliable core functionality while adapting to different platforms through configuration rather than code changes. Each module can be independently validated and certified.
3Productivity
If existing systems are designed with fixed architecture, then they achieve stability and reliability, but they require significant redevelopment effort for new missions
Solution Approach 1:
The system implements a dynamic software architecture that can be configured at runtime based on mission requirements. The parameterized algorithms allow the system to adapt its behavior dynamically without requiring structural changes to the codebase. New missions can be implemented by loading different parameter sets rather than developing new software architectures.
Data Source
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Figure 1c
Figure 2a
AI summary
An autonomy system for use with a vehicle in an environment. The autonomy system comprising a processor operatively coupled with a memory device, a plurality of sensors operatively coupled with the processor; a vehicle controller, a situational awareness module, a task planning module, and a task execution module. The situational awareness module being configured to determine a state of the environment based at least in part on sensor data from at least one of the plurality of sensors. The task planning module being configured to identify, via the processor, a plurality of tasks to be performed by the vehicle and to generate a task assignment list from the plurality of tasks that is based at least in part on predetermined optimization criteria. The task execution module being configured to instruct the vehicle controller to execute the plurality of tasks in accordance with the task assignment list. The task execution module may be configured to monitor the vehicle or the vehicle controller during execution of the task assignment list to identify any errors.