MATT can secure devices on a tilting platform that can incline up to a 30-degree angle. This can switch the device from landscape to portrait mode, a capability that allows complex AR and VR application testing.
MATT can tackle any tests that require physical input. Test device human-machine interface buttons, switches, knobs, keyboards, volume rockers, sleep/wake, and operability with other controls independently and in any combination. It can press physical buttons, side buttons, and any other data input form. The testing robot will be an excellent tool for any product where the input cannot be easily simulated, like PoS or systems where the same input must be introduced multiple times.
Many of the interactions with a touchscreen can be simulated with software test automation frameworks like Selenium, Appium, as well as OS-specific testing software like ESPRESSO UI (Android), XC testing (iOS), but due to the wide variety of hardware devices, this can be a complicated task. However, MATT manages both hardware and software interaction with ease. Due to MATT’s flexibility, it can be integrated into any testing framework. Therefore, synchronization between software testing automation and hardware button pressing can be achieved seamlessly.
MATT can be equipped with an external high-speed camera for different measurements. Moreover, the speed of up to 2m/s ensures that the robot can reach any point swiftly and with high accuracy.
Building on high accuracy, MATT moves with 0.05mm precision and touches with exact pressure, capabilities that make the robot an ideal tool, effective in touch screen device calibration and not only. To better fit use cases, the capacitance, size and shape of MATT fingers can be customized.
The robot automates the pressing of any buttons, placed vertically or sideways, and interact with any touch screen devices (resistive or capacitive).
MATT is a flexible asset, whose potential can be directed towards the specific test automation and device calibration needs of a company and supports every use case.
MATT’s design is focused on modularity; for this reason, the hardware platform and the test sequence software API can be seen as different parts. Depending on the application, MATT can be employed as an embedded device testing tool, performing basic, yet powerful tasks, or as a complete, unified robotic test automation solution.
MATT’s cross-platform software architecture allows it to easily integrate with frameworks dedicated to Machine Learning for image processing. One successful example is Intel’s OpenVINO toolkit, which has enabled MATT to solve captcha tasks, such as selecting cars from a collection of distinct images. Regarding integration with Artificial Intelligence or Machine Learning Frameworks, MATT’s applications are unlimited.
From device production quality assurance testing and performing calibration testing, to software and app testing, MATT offers all the functionalities underlying every aspect of HMI physical device testing.
Advanced users can reference the extensive, low-level serial protocol documentation to obtain maximum control over the system’s movements and trajectories. The embedded, industrial USB3 Vision camera is accessible to third-party computer vision toolkits like NI Vision Builder™, OMRON AutoVision™ and many more.
Every MATT robot can be controlled independently, on the network, using the included software suite. Its powerful and easy-to-use Python API offers adaptability in controlling the testing process in both multi-robot and multi-device scenarios simultaneously, achieving unmatched flexibility.
“MATT’s idea was born as soon as we faced the challenge of testing multiple devices and their constant software updates quickly and accurately. None of the available tools were fully capable of satisfying our demand for efficiency, which is the same demand of many other companies. We decided to build it ourselves, starting from our in-depth knowledge of the processes and requirements, creating a machine that would qualify in terms of reliability, accuracy and scalability.”
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