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slip_detection_dataset_2021

The dataset contains tactile data collected during outdoor autonomous robot pick‑and‑place tasks. Data were collected by an EZGripper attached to a Universal Robot UR5 arm, using a uSkin tactile sensor measuring normal and shear forces at 180 Hz. The dataset includes grasp data for three different objects (solder spool, brush, screwdriver) in various poses, each pose repeated ten times, totaling 30 grasps per object.

Updated 12/28/2021
github

Description

Dataset Overview

Dataset Name

slip_detection_dataset_2021

Data Collection Environment

The dataset contains tactile data collected during autonomous robot grasping and placing tasks.

Data Collection Equipment

  • Robot Arm and Gripper: EZGripper mounted on a Universal Robot UR5 arm.
  • Tactile Sensor: One finger of the EZGripper was replaced with a dedicated structure containing a uSkin tactile sensor.
  • Vision Sensor: Kinect2 positioned above the workbench for autonomous grasp generation.

Tactile Sensor Characteristics

  • Sensor Type: uSkin sensor.
  • Number of Sensory Points: 18 points arranged 3×6.
  • Sampling Frequency: 180 Hz.
  • Measurement Capability: Each point independently measures applied normal and shear forces.

Dataset Content

  • Number of Objects: 3 (solder spool, brush, screwdriver).
  • Object Poses: Each object placed in three different poses within a 50 cm × 50 cm workspace.
  • Experiment Repetitions: Each pose repeated ten times, yielding 30 grasps per object.

Data Storage Format

Data are stored in HDF5 files, one file per object.

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Topics

Robotics
Tactile Sensing

Source

Organization: github

Created: 3/6/2021

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