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3D Mixed Reality (MR) Human-Robot Interfaces (HRI) show promise for robotic operators to complete tasks quicker, safer and with less training. In this talk, the use of 3D MR HRI environment will be presented and compared with a standard 2D Graphical User Interface (GUI) in order to control a redundant 9 DOF mobile manipulator. The robotic manipulator has been mounted in a robotized train, the CERN Train Inspection Monorail (TIM), used for many inspection tasks and for the Beam Loss Monitor (BLM) robotic measurement in a complex hazardous intervention scenario at CERN. The use case of point cloud real time and reconstruction information for 3D feedback and collision avoidance or detection will be demonstrated. The NASA TLX method of efficiency and workload measurement of an operator, and operator condition monitoring techniques, such as heart rate, Galvanic Skin Response parameters and stress monitoring, will be discussed. An automatic detection and pose estimation with the use of the BLMs and SPS accelerator door tracking and visual servoing will be introduced, as an example of machine learning and AI in robotics at CERN.
Short Bio Krzysztof Adam Szczurek
Krzysztof Adam Szczurek received the M.Sc. Eng. degree in Control Engineering and Robotics (2017) from the Wrocław University of Science and Technology (Poland). Currently he is pursuing the Ph.D. degree at the Jaume I University of Castellon (Spain) in Computer Science and Robotics. From 2013 to 2014 he worked in American Axle & Manufacturing on industrial controls for the automotive sector. In 2017 he worked in Nokia on the 5G communication technology. From 2015 to 2016 and after since 2017 he has been with CERN, working on automation, control software and robotics projects. He is passionate about Mixed Reality Human-Robot Interfaces, and specialized in design and implementation of control systems consisting of complex and state-of-the-art solutions, based on PLC/SCADA and Real-Time Systems (C++/C#/Unity and LabVIEW).
Massimo Giovannozzi / Participants 70