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Computer vision based object grasping 6DoF robotic arm using picamera

  • Vishal Kumar
  • , Qiang Wang
  • , Wang Minghua
  • , Syed Rizwan
  • , S. M. Shaikh
  • , Xuan Liu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This article presents a project to design a robust robotic arm which can perform multifunctional tasks. The controller of the manipulator is based on Arduino mega 2560 Microcontroller. The aim of the project is to focus all axes of manipulator to lift, carry and unload the objects at a desired location. This requires a precise drive motion control that incorporate electric motors as a drive system. Further experiments are done to implement a camera based 3D vision system integrated with a computer vision algorithm to recognize object deformation and spatial coordination to control the deviation from the original training. The 3D visualization systems are able to detect the objects as well as their distance from the End-effecter and transmit the signals to the drive system. The vision system requires a separate computing hardware capable of processing complex vision algorithms. We utilize Raspberry pi microcontroller for processing the vision data, separately making the vision system capable of recognizing the specified object as per program commands.

Original languageEnglish
Title of host publicationProceedings - 2018 4th International Conference on Control, Automation and Robotics, ICCAR 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages111-115
Number of pages5
ISBN (Electronic)9781538663387
DOIs
StatePublished - 13 Jun 2018
Event4th International Conference on Control, Automation and Robotics, ICCAR 2018 - Auckland, New Zealand
Duration: 20 Apr 201823 Apr 2018

Publication series

NameProceedings - 2018 4th International Conference on Control, Automation and Robotics, ICCAR 2018

Conference

Conference4th International Conference on Control, Automation and Robotics, ICCAR 2018
Country/TerritoryNew Zealand
CityAuckland
Period20/04/1823/04/18

Keywords

  • color detection
  • computer vision system
  • object recognition
  • robotic arm

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