Evaluating Recipes Generated from Functional Object-Oriented Network
Abstract
The functional object-oriented network (FOON) has been introduced as a knowledge representation, which takes the form of a graph, for symbolic task planning. To get a sequential plan for a manipulation task, a robot can obtain a task tree through a knowledge retrieval process from the FOON. To evaluate the quality of an acquired task tree, we compare it with a conventional form of task knowledge, such as recipes or manuals. We first automatically convert task trees to recipes, and we then compare them with the human-created recipes in the Recipe1M+ dataset via a survey. Our preliminary study finds no significant difference between the recipes in Recipe1M+ and the recipes generated from FOON task trees in terms of correctness, completeness, and clarity.
Keywords
Cite
@article{arxiv.2106.00728,
title = {Evaluating Recipes Generated from Functional Object-Oriented Network},
author = {Md Sadman Sakib and Hailey Baez and David Paulius and Yu Sun},
journal= {arXiv preprint arXiv:2106.00728},
year = {2021}
}
Comments
This manuscript has been accepted at Ubiquitous Robots 2021