Knowledge Retrieval Using Functional Object-Oriented Networks

TL;DR

This paper introduces the FOON knowledge representation model for robotic tasks, detailing its structure, creation process, and search algorithms, demonstrating its effectiveness in object retrieval within robotic task planning.

Contribution

The paper presents a novel FOON model for robotic knowledge representation, including its structure, dataset creation, and search algorithms, advancing robotic task understanding.

Findings

Effective search algorithms demonstrated for object retrieval

Universal FOON dataset created for robotic tasks

Analysis of algorithm effectiveness in various scenarios

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.