Skip to content

Dataset for our paper "Towards Effective Tactile Identification of Textures using a Hybrid Touch Approach" (ICRA 2019)

Notifications You must be signed in to change notification settings

clear-nus/TactileLearning

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

26 Commits
 
 
 
 
 
 

Repository files navigation

Tactile Learning

Tactile Datasets

Supplementary material and dataset for the "Towards Effective Tactile Identification of Textures using a Hybrid Touch Approach", T. Taunyazov et al.

Dataset description

This dataset contains tactile sensor data 23 textures. The data are gathered from iCub's forearm tactile sensor for touch and slide. Each object has 3 folders:

  1. slide_raw
  2. touch_raw (only 10 samples)
  3. touch_raw2

Each folder there contains 3 folders:

  1. right_arm_encoders: encoder values of 15 dof of iCub's right arm
  2. right_forearm_comp: tactile sensor values
  3. skin_events: force values

These are objects' ids used in the paper:

  • BT -> bathTowel
  • CB -> cardBoard
  • PM -> carpetNet
  • CC -> cork
  • CH -> cotton
  • FM -> cuisionFoam
  • CS -> denim
  • ES -> eva
  • LC -> fakeLeather
  • FL -> felt
  • FB -> fiberBoard
  • MS -> metal
  • RS -> paper1
  • LM -> paper2
  • PS -> polypropileno
  • CT -> polypropilenoSmooth
  • BM -> softMaterial1
  • CP -> softMaterial2
  • SS -> spongeWhiteSmall
  • PF -> styrofoam
  • WP -> thinPolypropylene
  • BD -> woodHard
  • YM -> yogaMat

Materials with IDs

About

Dataset for our paper "Towards Effective Tactile Identification of Textures using a Hybrid Touch Approach" (ICRA 2019)

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published