Integrated Test Automation for Evaluating a Motion-Based Image Capture System Using a Robotic Arm

The problem discussed in this paper is how to create an integrated test automation setup, in which the test engineer does not have to use a pendant to communicate with the robotic arm and a separate test script to trigger on-device test automation for testing computer vision algorithms, such as motion-based image capture. There is no communication between the pendant to control the robotic arm and the test script that launches the on-device test automation for the motion-based image capture system executing on a mobile phone. Therefore, the test engineer needs to manually trigger the programs for the robot pendant to start the robotic arm, the automation, and launch times to keep them in sync. The solution to this problem is to design a test automation program using a middleware software (such as ORiN2 middleware software provided by Denso Robotics) to bypass the dependency on the robotic pendant, which must be manually started. The programmatic usage of the ORiN2 software also helps to establish a communication between the lab computer and a robot controller. The controller access object is used by the ORiN2 middleware software to communicate with the robotic controller of a Denso robot. It directly controls the robotic arm motion by accessing the programming variables. The image capture accuracy is calculated based on the number of snapshots and the similarity of the snapshots taken if the mobile phone under test is stationary and a motion is injected in the test subject. We compared the test results of the hardware-accelerated solution with a third-party solution, and found that the hardware accelerated solution is 12% more accurate for image capture accuracy at a medium panning speed. This paper discusses the integrated test automation framework for testing motion-based image capture system using a robotic arm.