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| en:safeav:as:refarchitectures [2025/10/17 09:12] – [ROS and ROS 2 Framework] agrisnik | en:safeav:as:refarchitectures [2025/10/17 09:21] (current) – [MOOS-IvP Architecture for Marine Systems] agrisnik | ||
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| The ROS 2 architecture provides several advantages, including component-level independence from the provider, modularity enabling easier development as well as large community and libraries of packages for deployment. ROS 2 is now the backbone for major open-source projects such as Autoware.AI (autonomous driving) and PX4-Autopilot (UAV control). | The ROS 2 architecture provides several advantages, including component-level independence from the provider, modularity enabling easier development as well as large community and libraries of packages for deployment. ROS 2 is now the backbone for major open-source projects such as Autoware.AI (autonomous driving) and PX4-Autopilot (UAV control). | ||
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| + | ===== AUTOSAR Adaptive Platform ===== | ||
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| + | In the automotive sector, the AUTOSAR (AUTomotive Open System ARchitecture) standard defines a scalable, service-oriented architecture supporting high-performance applications such as automated driving ((AUTOSAR Consortium. (2023). AUTOSAR Adaptive Platform Specification. AUTOSAR)). | ||
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| + | <figure AUTOSAR Adaptive Platform Overview > | ||
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| + | The AUTOSAR Adaptive Platform is conceptually a middleware. AUTOSAR Adaptive Platform provides services to Adaptive Applications beyond those available from the underlying operating system, drivers, and extensions. One of the distinctive features of the AUTOSTAR is its Real-time and safety-critical compliance (ISO 26262) as well as use of SOME/IP and DDS for service-based communication purposes. AUTOSAR is widely implemented in production autonomous vehicles from manufacturers like BMW, Volkswagen, and Toyota ((Broy, M., et al. (2021). Modeling Automotive Software Architectures with AUTOSAR. Springer)). | ||
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| + | ===== JAUS – Joint Architecture for Unmanned Systems ===== | ||
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| + | The JAUS (Joint Architecture for Unmanned Systems) is a U.S. Department of Defense standard (SAE AS5669A) defining a message-based, | ||
| + | JAUS defines: | ||
| + | * A component-based hierarchy (Subsystem → Node → Component → Service) | ||
| + | * Standardised message sets for communication | ||
| + | * Cross-domain interoperability | ||
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| + | <figure JAUS Component Hierarchy > | ||
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| + | JAUS remains influential in defence and research projects where multiple unmanned vehicles must coordinate under a unified framework. Due to its straightforward and easy-to-implement architecture, | ||
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| + | ===== MOOS-IvP Architecture for Marine Systems ===== | ||
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| + | MOOS (Mission Oriented Operating Suite) combined with IvP (Interval Programming) forms a robust architecture for marine autonomy, developed at MIT and used in NATO and U.S. Navy programs ((Benjamin, M. R., Curcio, J. A., & Leonard, J. J. (2012). MOOS-IvP autonomy software for marine robots. Journal of Field Robotics, 29(6), 821–835)). | ||
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| + | <figure MOOS-IvP Architecture > | ||
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| + | IvP (Interval Programming) Helm provides decision-making capabilities based on models provided by the developers, while MOOS DB provides access to data and decisions collected by Applications. Client applications (or just Applications are the main functionality, | ||
| + | All of the mentioned allow an asynchronous behaviour-based response to a changing environment and higher flexibility, | ||
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| + | ===== Comparative Summary of Reference Architectures ===== | ||
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| + | ^ Architecture ^ Domain ^ Key Features ^ Communication Model ^ | ||
| + | | ROS / ROS 2 | General / Research | Modular, open-source, | ||
| + | | AUTOSAR Adaptive | Automotive | Safety, real-time, standardised | Service-oriented (SOME/IP, DDS) | | ||
| + | | JAUS | Defence / Multi-domain | Interoperability, | ||
| + | | MOOS-IvP | Marine | Behaviour-based, | ||
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| + | Recent trends combine multiple reference architectures to exploit their strengths. For example: | ||
| + | * **ROS–AUTOSAR** bridges enable integration between experimental and production-grade systems. | ||
| + | * **DDS–MQTT** hybrids connect real-time robotics with cloud-based IoT analytics. | ||
| + | * **ROS–MOOS** integrations allow cross-domain cooperation between underwater and surface robots ((Petillot, Y., et al. (2020). Underwater robotics: Hybrid autonomy and AI integration. Annual Reviews in Control, 50, 238–254)). | ||
| + | Such hybridization reflects the growing need for flexibility and cross-domain interoperability in modern autonomous systems. | ||
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