Autonomy Transfer

Autonomy transfer focuses on enabling autonomous systems to rapidly adapt to new environments or tasks with minimal retraining. Current research emphasizes efficient knowledge transfer techniques, such as leveraging pre-trained models and incorporating human expertise (e.g., through learning from demonstration), to accelerate this adaptation process. This is crucial for improving the robustness and applicability of autonomous systems across diverse domains, from robotics and autonomous driving to multi-robot coordination and subterranean exploration. The development of algorithms that facilitate faster and more reliable autonomy transfer is a key challenge with significant implications for the safety and efficiency of autonomous technologies.