How to use Sensor Glove with Robot Hand

Repository Clone

 

Additional Requirements

Connection with PC

First step is to make sure that the Sensor glove is connected to the USB0 and Robot Hand is connected to USB1. If this is not in order, we might have to change it inside the files and aslo in rosserial_python library. 

Connecting with ROS

  • Initiate Roscore with command: roscore
  • Run the Rosserial Python command to initiate the Serial connection between with the hand through Python:

          rosrun rosserial_python serial_node.py tcp

           You will see something like this:

  • After this, run the Arduino file to initiate the calibration. If the Serial connection is finished, you will see something like this:

Connecting with the Robot Hand

In order to connect with the hand, just run this file:

roslaunch rh8d start_rh8d.launch

Meeting Notes 13.10.2021

Meeting Details

Date : 13th October 2021

Time : 12:30 – 13:00

Location : Chair of CPS, Montanuniverität Leoben

Participants: Univ.-Prof. Dr. Elmar Rueckert, Vedant Dave

Agenda

Tactile Sensing approach description and hand implementation

Topic 1: Implementation of Robotic hand in the Manipulator and Data acquisition

  1. Data acquisition from robotic gripper
  2. Repeatability check for same grasp configuration

Topic 2: Implement Existing Algorithm

Implement any existing algorithm when the robotic hand implementation is done. This needs to be discussed later.

Next Steps

  1. Attach the Robot hand to the Manipulator.
  2. Collect the tactile data for different objects and check repeatability of data.

Literature

Tactile Data Prediction from Tactile Sensing and Computer Vision without touch

  1. B. S. Zapata-Impata, P. Gil, Y. Mezouar and F. Torres, “Generation of Tactile Data From 3D Vision and Target Robotic Grasps,” in IEEE Transactions on Haptics, vol. 14, no. 1, pp. 57-67, 1 Jan.-March 2021, doi: 10.1109/TOH.2020.3011899.

Tactile Data Prediction on Novel objects through Touch

  1. Z. Abderrahmane, G. Ganesh, A. Crosnier and A. Cherubini, “A Deep Learning Framework for Tactile Recognition of Known as Well as Novel Objects,” in IEEE Transactions on Industrial Informatics, vol. 16, no. 1, pp. 423-432, Jan. 2020, doi: 10.1109/TII.2019.2898264. 
  2. Zambelli, M., Aytar, Y., Visin, F., Zhou, Y., & Hadsell, R. (2021). Learning rich touch representations through cross-modal self-supervision. ArXiv, abs/2101.08616.

Tactile knowledge

  1.  M. Kaboli, R. Walker and G. Cheng, “Re-using prior tactile experience by robotic hands to discriminate in-hand objects via texture properties,” 2016 IEEE International Conference on Robotics and Automation (ICRA), 2016, pp. 2242-2247, doi: 10.1109/ICRA.2016.7487372.

Next Meeting

Next meeting will take place on Thursday, 21st August, 2021. 01:00 pm – 02:00 pm.