AI-Augmented Software Engineering for Intelligent Robotics
Modern robots operate in complex and unpredictable environments and increasingly rely on AI to learn and make decisions. This makes robotics software harder to design, verify, and maintain with traditional engineering methods. ASTIR addresses this challenge by integrating trustworthy generative AI into every stage of the robotics software engineering lifecycle, from requirements engineering to system maintenance. The open-source, AI-augmented workbench aims to improve productivity, collaboration, and reliability in robotics development. The project will validate its technology through three open-access use cases in service robotics, manufacturing robotics, and drone systems.

Trustworthy GenAI for Software Engineering
ASTIR sets out to bolster the trustworthiness of GenAI models, with a focus on LLMs, so that they can be used for the engineering of intelligent robots.

Generative AI-Augmented Software Engineering for Intelligent Robotics: From Concept to Code
ASTIR harnesses AI to automate the generation, analysis, and validation of functional and non-functional requirements for robotics systems, creating novel AI tools to extract requirements from various information sources and generate detailed specifications.

Generative AI-Augmented Software Engineering for Intelligent Robotics: Dependability Assurance
ASTIR leverages LLMS to enhance software development security and reliability through the creation of AI-based tools for code review, test case generation, and monitoring.
