# Knowledge Retrieval for Robotic Cooking

arXiv: https://arxiv.org/abs/2211.04524 · HTML: https://mlsanity.com/paper/2211.04524/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 13 references that are in the map.
- First posted on arXiv 8 Nov 2022.

## Builds on (most cited first, 4 of 4)

- [Functional Object-Oriented Network for Manipulation Learning](https://mlsanity.com/paper/1902.01537/) (2019)
- [Functional Object-Oriented Network: Construction & Expansion](https://mlsanity.com/paper/1807.02189/) (2018)
- [Approximate Task Tree Retrieval in a Knowledge Network for Robotic Cooking](https://mlsanity.com/paper/2207.03693/) (2022)
- [Evaluating Recipes Generated from Functional Object-Oriented Network](https://mlsanity.com/paper/2106.00728/) (2021)

## Abstract (arXiv)

Search algorithms are applied where data retrieval with specified specifications is required. The motivation behind developing search algorithms in Functional Object-Oriented Networks is that most of the time, a certain recipe needs to be retrieved or ingredients for a certain recipe needs to be determined. According to the introduction, there is a time when execution of an entire recipe is not available for a robot thus prompting the need to retrieve a certain recipe or ingredients. With a quality FOON, robots can decipher a task goal, find the correct objects at the required states on which to operate and output a sequence of proper manipulation motions. This paper shows several proposed weighted FOON and task planning algorithms that allow a robot and a human to successfully complete complicated tasks together with higher success rates than a human doing them alone.