The service focuses on testing, benchmarking, and technical performance evaluation of advanced industrial 2D and 3D machine vision camera systems. It includes evaluation of standalone 3D sensors, sensor fusion of 2D and 3D data, and the use of AI-driven Deep Learning for 6D pose estimation and localizing unknown objects in bins for robotic picking. The purpose is to help customers understand, compare, and validate camera technologies and AI methods for demanding industrial tasks such as high-speed assembly, random bin picking, and automated quality inspection where accurate object detection, positioning, and robust perception are critical. Type of service: Experiment / Applied R&D and Demonstration
A documented evaluation of relevant 2D and 3D camera technologies and AI methods, including performance measurements, application assessment, and recommendations for further development or implementation. The service delivers quantifiable benefits by reducing customer R&D risk and integration time by up to 40% through pre-validated hardware/software stacks and targeting picking success rates above 98%. As demonstrated in previous industrial metal parts and automotive handling projects, this process successfully de-risks random bin picking and accelerates deployment from TRL 3 to validated factory-floor demonstrators.
The service is delivered as a structured experimental process including use-case clarification, selection and testing of 2D and 3D camera technologies, evaluation of 2D/3D fusion, testing of Deep Learning for object detection and localization, and delivery of documented results and recommendations.
Manufacturing, Robotics and automation, Picking and handling, Logistics and intralogistics, Other emerging and enabling technologies