FOON Creation and Traversal for Recipe Generation

TL;DR

This paper presents a method for creating and traversing functional object-oriented networks (FOON) to enable robots to generate recipes by planning sequences of actions based on network traversal techniques.

Contribution

It introduces a process for constructing FOONs from human input and demonstrates traversal methods for recipe generation in robotic task planning.

Findings

FOON can be created from human-annotated text files.

Network traversal enables recipe generation through various search strategies.

The approach facilitates robotic task planning for cooking tasks.

Abstract

Task competition by robots is still off from being completely dependable and usable. One way a robot may decipher information given to it and accomplish tasks is by utilizing FOON, which stands for functional object-oriented network. The network first needs to be created by having a human creates action nodes as well as input and output nodes in a .txt file. After the network is sizeable, utilization of this network allows for traversal of the network in a variety of ways such as choosing steps via iterative deepening searching by using the first seen valid option. Another mechanism is heuristics, such as choosing steps based on the highest success rate or lowest amount of input ingredients. Via any of these methods, a program can traverse the network given an output product, and derive the series of steps that need to be taken to produce the output.