How Continual Learning and Generative AI are transforming Robotics

Continual Learning (CL) and Generative AI (GenAI) are two of the most transformative developments in modern machine learning. CL equips systems with the ability to learn from sequential data over time without catastrophic forgetting, while GenAI - through Large Language and Vision Models, diffusion models, and other generative architectures - is redefining how robots perceive, reason, and act with minimal supervision. This workshop aims to explore the intersection of CL and GenAI in the context of robotics, focusing on how these paradigms can be effectively integrated to enable long-term autonomy, adaptability, and scalable intelligence. We will also address the key challenges of deploying these technologies in embodied systems, including computational constraints, safety considerations, and the need for robust generalization in the real world. Topics of interest include: (i) continual learning algorithms tailored for robotics, (ii) generative models for perception, planning, and control, (iii) benchmarks and evaluation protocols, and (iv) real-world applications across service, assistive, and industrial robotics. The workshop will feature invited talks, a poster and pitch session, and an open discussion to foster collaboration between the AI and robotics communities.