Task Tree

Task trees represent structured sequences of actions for robots to complete complex tasks, primarily focusing on improving the reliability and efficiency of robotic planning. Current research emphasizes generating these trees from various knowledge sources, including large language models (LLMs) and functional object-oriented networks (FOONs), often employing search algorithms like iterative deepening depth-first search (IDS) and greedy best-first search (GBFS) to navigate these knowledge representations and optimize for accuracy and cost. This work is significant for advancing robotic autonomy, particularly in domains like cooking, where flexible adaptation to novel situations and efficient task execution are crucial.