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.

本文主要介绍了针对机器人执行任务时需要的数据检索和算法设计，提出了一些加权功能对象网络和任务规划算法，能够使机器人和人类成功地共同完成比人类单独完成更复杂的任务。

机器烹饪知识检索

Knowledge Retrieval for Robotic Cooking

We investigate the problem of coordinating two robot arms to solve
non-monotone tabletop multi-object rearrangement tasks. In a non-monotone
rearrangement task, complex object-object dependencies exist that require
moving some objects multiple times to solve an instance. In working with two
arms in a large workspace, some objects must be handed off between the robots,
which further complicates the planning process. For the challenging dual-arm
tabletop rearrangement problem, we develop effective task planning algorithms
for scheduling the pick-n-place sequence that can be properly distributed
between the two arms. We show that, even without using a sophisticated motion
planner, our method achieves significant time savings in comparison to greedy
approaches and naive parallelization of single-robot plans.

研究使用两个机器臂解决多物体重新排列的问题，并开发了有效的任务规划算法来安排拾取和放置序列，以节省时间和提高效率。