Observable Robotic

Observable robotics focuses on enabling robots to effectively operate in environments where complete information is unavailable, requiring them to plan actions based on incomplete or uncertain observations. Current research emphasizes developing algorithms that integrate planning with perception, leveraging techniques like hierarchical planning, reinforcement learning guided by logical specifications, and the use of large language models for interactive planning and state inference. These advancements aim to improve robot robustness and adaptability in real-world scenarios, impacting fields such as human-robot interaction and safe autonomous navigation.