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About

Konrad Gac is a robotics and control systems researcher whose work sits at the intersection of advanced robotics, CNC machining, and hardware-accelerated computation. His research focuses primarily on hybrid and parallel robot systems designed for precision milling applications, with particular emphasis on motion control, kinematics, and trajectory generation. Gac has made notable contributions to the development of CNC control architectures for complex robotic systems. His 2016 papers on 5-axis hybrid robot milling — covering both CNC system design and trajectory tracking control — each garnered 20 citations, establishing him as a meaningful voice in the field of robot-assisted manufacturing. Earlier work from 2012 and 2013 demonstrated his innovative application of Field Programmable Gate Arrays (FPGAs) to accelerate computationally demanding tasks such as inverse kinematics and trajectory generation for parallel robots. His most-cited FPGA paper (2012, 15 citations) tackled the challenge of real-time Cartesian-space trajectory execution — a problem central to practical CNC robotics. Across his body of work, Gac consistently bridges theoretical control challenges with hardware implementation, making his research particularly valuable to engineers and researchers developing next-generation intelligent manufacturing and robotic machining systems.