A Hybrid Image Based Visual Servoing for a Manipulator using Kinect

R. Raja, S. Kumar

Research output: Chapter in Book/Report/Conference proceedingConference proceeding (ISBN)

1 Citation (Scopus)

Abstract

In this paper, we propose a hybrid image based visual servoing for 6 degrees of freedom (DoF) robot manipulators. It avoids the drawbacks of classical position-based visual servoing. Contrary to the position-based visual servoing, this method does not require any knowledge of the geometric 3 DoF model of the object. On the other hand, the depth information of the object is required. In the proposed approach, a Kinect sensor is used as a camera, which provides depth information of the object from the point cloud. .is method tracks the position of the target object. .e method is simulated in Gazebo platform with Kinect sensor mounted on 6 DoF Universal Robot 5 (UR5) manipulator, where all the physical parameters of the robot and Kinect sensor is considered. .e solution is developed in C++ integrated with ROS, OpenCV. .e method illustrated with a variety of simulation results with an eye-in-hand robotic system which shows the convergence of the system and potential of our method.

Original languageEnglish
Title of host publicationProceedings of the Advances in Robotics, AIR 2017
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450352949
DOIs
Publication statusPublished - 28 Jun 2017
EventConference on Advances in Robotics, AIR 2017 - New Delhi, India
Duration: 28 Jun 20172 Jul 2017

Publication series

NameACM International Conference Proceeding Series
VolumePart F132085

Conference

ConferenceConference on Advances in Robotics, AIR 2017
CountryIndia
CityNew Delhi
Period28/06/172/07/17

Keywords

  • Eye-in-hand system
  • Gazebo
  • Image based visual servoing
  • Kinect sensor
  • UR5 robot manipulator

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  • Cite this

    Raja, R., & Kumar, S. (2017). A Hybrid Image Based Visual Servoing for a Manipulator using Kinect. In Proceedings of the Advances in Robotics, AIR 2017 [a52] (ACM International Conference Proceeding Series; Vol. Part F132085). Association for Computing Machinery. https://doi.org/10.1145/3132446.3134916