Data for: MOGrip: Gripper for multi-object grasping in pick-and-place tasks using translational movements of fingers

Humans utilize their dexterous fingers and adaptable palms in various multi-object grasping strategies to efficiently move multiple objects together in various situations. Advanced manipulation skills, such as finger-to-palm translation and palm-to-finger translation, enhance dexterity in multi-object grasping. These translational movements allow the fingers to transfer the grasped objects to the palm for storage, enabling the fingers to freely perform various pick-and-place tasks while the palm stores multiple objects. However, conventional grippers, although able to handle multiple objects simultaneously, lack this integrated functionality, which combines the palm's storage with the fingers' precise placement. Here, we introduce a gripper for multi-object grasping that applies translational movements of fingertips to leverage the synergistic use of fingers and the palm for enhanced pick-and-place functionality. The proposed gripper consists of four fingers and an adaptive conveyor pal..., Experiments To validate the motion of the decoupling design, the grasping tendon was pulled with a motor (100:1 Micro Metal Gearmotor HPCB 6V, Pololu). The movement of five different decoupling linkages was recorded by a camera with 30 fps, and the positions of the three red markers of each frame were tracked through MATLAB (MathWorks). The MATLAB function “imfindcircle” was utilized to find the red markers, and through the positions of these three markers, the rotation angle and translation distance of the finger were calculated. Experiments for each decoupling link design were repeated five times. The storing force along the y-axis was measured by a tensile testing machine (INSTRON 5948 Microtester). In the experiment measuring the storing force for a single object, to ensure repeatability in the process of inserting the object into the storage, the storage was divided in half and placed on both sides of the rail. Then, the target was placed between the storages, and stored by moving ..., , # Data for: MOGrip: Gripper for multi-object grasping in pick-and-place tasks using translational movements of fingers [https://doi.org/10.5061/dryad.44j0zpcqd](https://doi.org/10.5061/dryad.44j0zpcqd) ## Description of the data and file structure **Overview** This dataset contains the experimental data, modeling, and simulation model for analyzing the proposed gripper that can be applied to multi-object grasping in various pick-and-place tasks by using translational movements of fingers. The presented dataset is necessary for generating figures, models, and results for the paper titled \"MOGrip: Gripper for Multi-Object Grasping in Pick-and-Place Tasks Using Translational Movements of Fingers\". ### Files and variables #### File: ABAQUS\_Simulation.zip **Description:** INP files for running ABAQUS simulations with varying design parameters of the conveyor palm are provided. Although we intended to include all ODB files containing the simulation results, each file is approximatel...人类依靠灵巧的手指与适配性手掌，采用多种多物体抓取（multi-object grasping）策略，在各类场景中高效地同时搬运多个物体。诸如指掌间平移（finger-to-palm translation）与掌指间平移（palm-to-finger translation）这类高级操作技能（advanced manipulation skills），可提升多物体抓取的灵巧性。这类平移运动能够让手指将已抓取的物体转移至手掌进行收纳，使手指得以解放，在手掌收纳多个物体的同时自由执行各类拾取与放置（pick-and-place）任务。然而，传统夹持器（gripper）虽可同时处理多个物体，却缺乏将手掌收纳与手指精准放置相结合的集成功能。在此，我们提出一款面向多物体抓取的夹持器（gripper），其通过指尖的平移运动（translational movements of fingertips），实现手指与手掌的协同运作，以增强拾取与放置功能。所提出的夹持器由四根手指与一个自适应输送手掌组成……，实验部分如下： 为验证解耦设计（decoupling design）的运动性能，我们使用电机（100:1微型金属齿轮电机HPCB 6V，Pololu品牌）拉动抓取牵引索（grasping tendon）。以30fps帧率的相机记录五种不同解耦连杆机构的运动，并通过MATLAB（MathWorks公司）追踪每帧图像中三个红色标记点（marker）的位置。我们利用MATLAB的`imfindcircle`函数识别红色标记点，并通过这三个标记点的位置计算手指的旋转角度与平移距离。每种解耦连杆设计的实验均重复五次。 沿y轴方向的收纳力（storing force）通过拉力试验机（tensile testing machine，INSTRON 5948 Microtester）进行测量。在单个物体收纳力的测试实验中，为确保将物体插入收纳空间的过程具备可重复性，我们将收纳结构对半拆分并安装于导轨两侧。随后将待测物体放置于收纳结构之间，并通过移动…… # 数据关联：MOGrip：基于手指平移运动实现拾取放置任务的多物体抓取夹持器 DOI：https://doi.org/10.5061/dryad.44j0zpcqd ## 数据与文件结构说明 **概述** 本数据集包含用于分析所提出夹持器的实验数据、建模结果与仿真模型，该夹持器可通过手指的平移运动应用于各类拾取放置任务中的多物体抓取场景。本数据集可为论文《MOGrip：基于手指平移运动实现拾取放置任务的多物体抓取夹持器》的图表生成、模型构建与结果验证提供必要支撑。 ### 文件与变量 #### 文件：ABAQUS_Simulation.zip **描述：** 本文件包含用于运行ABAQUS仿真的INP文件，其中设置了输送手掌的不同设计参数。尽管我们计划纳入所有包含仿真结果的ODB文件，但每个文件大小约……