Knowledge Retrieval for Robotic Cooking

TL;DR

This paper presents search algorithms within Functional Object-Oriented Networks (FOON) to enable robots to retrieve recipes or ingredients efficiently, facilitating complex task execution alongside humans.

Contribution

It introduces weighted FOON and task planning algorithms that improve robotic and human collaboration success rates in complex tasks.

Findings

Robots can decipher task goals and identify objects in required states.

Proposed algorithms enable successful task completion with higher success rates.

Robots assist humans in executing complicated tasks more effectively.

Abstract

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.