A Dataset of Food Manipulation Strategies for Diverse Foods

A dataset of multimodal sensing modalities (forces, torques, poses, RGBD images) for acquiring bites of food. Includes a diverse set of food items, from vegetables like spinach and broccoli, to bready items like sandwiches and pizza, to thick items like mashed potatoes and jello, to composite items like noodles and rice & beans. This dataset extends "A Dataset of Food Manipulation Strategies" ( https://doi.org/10.7910/DVN/8TTXZ7 ) to a much more diverse set of food items.本数据集面向食物取食场景，采集了包含力、力矩、位姿及RGBD图像的多模态传感数据。数据集涵盖品类丰富的食物样本，包括菠菜、西兰花等蔬菜类，三明治、披萨等烘焙类食品，土豆泥、果冻等稠厚膏状食材，以及面条、米饭配豆类等复合食材。本数据集在《食物操作策略数据集》（https://doi.org/10.7910/DVN/8TTXZ7）的基础上，进一步扩充了食物品类的多样性覆盖。