Intelligent Autonomous Systems 16 - Proceedings of the 16th International Conference IAS-16
Intelligent Autonomous Systems 16 - Proceedings of the 16th International Conference IAS-16
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智能自治系统 16 - 第 16 届国际会议 IAS-16 论文集
DOI：
10.1007/978-3-030-95892-3_22
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发表时间：
2022
期刊：
影响因子：
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通讯作者：
Danno D
中科院分区：
文献类型：
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作者：
Danno D
机器人烹饪是一项艰巨的任务，因为从原始食谱指令到涉及精确运动和工具处理的机器人动作的翻译是具有挑战性的。本文介绍了自动配方技术识别的基础上记录的姿势轨迹的人类示威者进行煎饼食谱，作为一种直观的方法，未经训练的示威者展示机器人如何进行他们的食谱变体。Kinect 2传感器和OpenPose神经网络用于从演示中提取关键时间，当UR5手臂执行食谱时，这些时间会被复制。将几个人类烹饪的煎饼与机器人复制的煎饼进行比较，发现机器人的煎饼质量得分仅略低于人类，这表明所选的关键参数确实包含了烹饪技术中最重要的变化。此外，我们讨论了初步的结果，推断烹饪参数和质量分数之间的关系。
Robotic cooking is a difficult task, as the translation from raw recipe instructions to robotic actions involving precise motions and tool-handling is challenging. This paper introduces automated recipe technique recognition based on recording the pose trajectories of human demonstrators carrying out a pancake recipe, as an intuitive method for untrained demonstrators to show a robot how to carry out their recipe variant. A Kinect 2 sensor and the OpenPose neural network are used to extract key timings from the demonstrations, which are replicated when the recipe is carried out by a UR5 arm. Comparing several human-cooked pancakes with their robot-replicated counterparts, the robot’s pancake quality scores were found to be only slightly inferior to the human ones, suggesting that the key parameters selected did encompass the most important variations in cooking technique. Furthermore, we discuss preliminary results in inferring the relationship between the cooking parameters and the quality scores.