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

机译:集成测试自动化,用于使用机械臂评估基于运动的图像捕获系统

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摘要

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.
机译:本文讨论的问题是如何创建集成的测试自动化设置,其中测试工程师不必使用悬垂物与机械臂进行通信,而无需使用单独的测试脚本来触发设备上的测试自动化以测试计算机视觉算法,例如基于运动的图像捕获。在用于控制机械臂的控制盒和测试脚本之间没有通信,测试脚本启动了在手机上执行的基于运动的图像捕获系统的设备上测试自动化。因此,测试工程师需要手动触发机器人吊坠的程序,以启动机械臂,自动化和启动时间,以使其保持同步。解决此问题的方法是使用中间件软件(例如Denso Robotics提供的ORiN2中间件软件)设计测试自动化程序,以绕过对必须手动启动的自动悬架的依赖。 ORiN2软件的编程用法也有助于在实验室计算机和机器人控制器之间建立通信。控制器访问对象由ORiN2中间件软件用来与Denso机器人的机器人控制器进行通信。它通过访问编程变量直接控制机器人手臂的运动。如果被测移动电话静止并且在被测对象中注入了运动,则基于快照的数量和所拍摄快照的相似度来计算图像捕获的准确性。我们将硬件加速解决方案的测试结果与第三方解决方案进行了比较,发现在中等摇摄速度下,硬件加速解决方案的图像捕获精度要高出12%。本文讨论了使用机械臂测试基于运动的图像捕获系统的集成测试自动化框架。

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