Year: 2022
Type: preprint
Abstract: 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.
Source: arXiv (Cornell University)
Author: Laverghetta, Gabriel
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4310419201