Comprehensive study and investigation of ROS for computer vision applications using Raspberry Pi

  • Authors

    • Jignesh Patoliya Charotar university of science & technology
    • Hiren Mewada Charotar university of science & technology
  • Object tracking, Robot operating system, raspberry Pi
  • The machine in the form of the robots has a very large community which makes impressive progress in recent trends. Progressive examples of these types of robots are land based mobile robots, quadcopters, humanoid, etc. Motion tracking and object recognition is the base process in major robotic applications. For better flexibility and integration of robots with video processing applications, the ROS framework is largely used. The major issue with ROS is its latency and integrity. This paper investigates the integration of the ROS framework with OpenCV libraries on the Raspberry PI processor for video processing applications. In the proposed experiment setup, a camera node interfaced with the raspberry PI captures images and publishes it in ROS message form on a specific topic. The subscriber node converts ROS message into an image using cvbridge. Converted image is processed again using OpenCV library on the raspberry Pi board. The extracted information can be used to actuate peripheral devices interfaced with the raspberry Pi. An investigation of the raspberry Pi based implementation reveals that ROS introduces 0.63% overhead and optimum implementation on raspberry Pi can avoid the high configured computer and raspbeery Pi can process the video at 13 frames per second at most.

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  • How to Cite

    Patoliya, J., & Mewada, H. (2019). Comprehensive study and investigation of ROS for computer vision applications using Raspberry Pi. International Journal of Engineering & Technology, 8(3), 261-269.