Autonomous Operation

Autonomous operation research aims to create systems capable of self-managing and adapting to dynamic environments, encompassing robots, vehicles, and even computing systems. Current efforts focus on improving robustness and efficiency through techniques like reinforcement learning (including causal RL and deep RL), hierarchical planning, and the integration of large language models for decision-making and task automation. These advancements are crucial for enhancing safety and reliability in various sectors, from aviation and robotics to space exploration and nuclear power, enabling more efficient and adaptable systems in complex and unpredictable scenarios.