Structured Environment

Structured environments, encompassing settings with predictable rules and constraints, are a key focus in robotics, AI, and optimization research. Current work centers on developing algorithms and models, such as control barrier functions with model predictive control, and integrating deep reinforcement learning with rule-based systems, to enable efficient and robust navigation, manipulation, and decision-making within these environments. This research is crucial for advancing autonomous systems in various applications, including manufacturing, transportation, and exploration, by improving the reliability and adaptability of robots and AI agents in complex, yet structured, settings. Furthermore, understanding how to represent and reason over structured environments is improving the performance of large language models in knowledge-based tasks.