Knowledge Retrieval Using Functional Object-Oriented Networks
This work addresses knowledge retrieval for robotic agents performing object transformation tasks, but it appears incremental as it builds on existing FOON concepts without claiming major breakthroughs.
The paper tackled the problem of robotic task knowledge representation and retrieval by proposing the FOON model and evaluating search algorithms on a universal dataset, reporting on the effectiveness of each algorithm.
Robotic agents often perform tasks that transform sets of input objects into output objects through functional motions. This work describes the FOON knowledge representation model for robotic tasks. We define the structure and key components of FOON and describe the process we followed to create our universal FOON dataset. The paper describes various search algorithms and heuristic functions we used to search for objects within the FOON. We performed multiple searches on our universal FOON using these algorithms and discussed the effectiveness of each algorithm.