Knowledge-based Autonomous
Systems Laboratory

Autonomous Robots: Developing autonomous robots that exhibit awareness and adaptability in complex and uncertain environments, with a focus on applications such as mobile manipulation in retail, underwater autonomous vehicles, and self-awareness for tool making.

Cognitive Architectures: Advancing the field of cognitive robotics by exploring hybrid cognitive architectures inspired by biological awareness and utilizing model-based systems engineering to design and model intelligent control systems for autonomous robots.

Knowledge Representation: Innovating in knowledge representation and reasoning methods for autonomous systems, with a particular emphasis on developing novel approaches to address runtime uncertainty.

Systems Engineering: Applying model-based systems engineering methods to design and model the architectures of robotic systems, contributing to the development of reliable, trustworthy, and explainable robots.

Collaborative Research: Facilitating initiatives that bring together experts in autonomous robots, cognitive architectures, knowledge representation, and systems engineering to contribute to the collective understanding and advancement of the field.

Disruptive Innovation: Driving innovation in robotics by researching self-adaptive systems, motion planning for mobile manipulation, and the development of awareness architectures, ultimately aiming to create groundbreaking solutions with real-world applications.

Higher Education: Offering comprehensive courses in knowledge representation and symbolic reasoning, multidisciplinary projects, and electives in artificial intelligence, to prepare students for careers in robotics and autonomous systems at the master's levels.

Reliable Solutions: Focusing on methods and technologies to ensure the development of reliable autonomous robots, with an emphasis on addressing uncertainties.