{"id":190571,"date":"2025-11-25T13:29:17","date_gmt":"2025-11-25T12:29:17","guid":{"rendered":"https:\/\/eurecat.org\/portfolio-items\/dyccat\/"},"modified":"2025-11-25T13:36:08","modified_gmt":"2025-11-25T12:36:08","slug":"dyccat","status":"publish","type":"avada_portfolio","link":"https:\/\/eurecat.org\/en\/portfolio-items\/dyccat\/","title":{"rendered":"DYCCAT"},"content":{"rendered":"

\"DYCCAT<\/p>\n<\/div>

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Dynamic control cabin testing.<\/strong><\/p>\n

DYCCAT<\/strong> addresses the challenge of automating dynamic testing on train cab control desks<\/strong>, removing the need for precise pre-positioning.<\/p>\n

Through 3D vision and geometric registration algorithms, the system developed in DYCCAT recognises the geometry of the desk and accurately locates its controls<\/strong>, regardless of their initial position<\/strong>. This enables the robot to autonomously identify each element and intelligently manipulate the desk\u2019s controls.<\/p>\n

A key feature of DYCCAT is its flexibility: the solution is agnostic to the position and type of test desk, as long as its digital model is available<\/strong>. This allows for quick switching between different cabin models without manual reprogramming, significantly enhancing testing efficiency and repeatability.<\/p>\n

DYCCAT demonstrates the potential of robotics and advanced vision technologies to automate functional testing in the railway sector, contributing to greater efficiency and traceability in cab validation processes.<\/p>\n

DYCCAT is an initiative developed by Eurecat\u2019s Robotics and Automation Unit<\/a> in collaboration with Alstom<\/a>, as part of a proof of concept aimed at technological validation for railway applications.<\/p>\n