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About

Gregor Novak is a robotics researcher whose work has made meaningful contributions to the fields of autonomous mobile robotics, computer vision, and intelligent control systems. His research has centered on the design and development of miniaturized autonomous robots, most notably through the Tinyphoon platform — a remarkably compact two-wheeled differentially driven robot fitting within a 75mm cube — demonstrating that high-performance autonomy could be achieved at an exceptionally small scale. Novak's vision-related contributions have been particularly impactful, including the development of real-time image recognition systems capable of processing up to 60 frames per second on resource-constrained hardware, as well as stereo vision and line-based landmark recognition systems for robot self-localization. Much of this work was demonstrated within the competitive and technically demanding context of robot soccer, where path planning, cooperative behavior, and fast perception are critical. His neural network-based predictive trajectory tracking further showcases an interest in intelligent, learned control strategies. Extending beyond mobile robotics, Novak also explored optimized control methods for Cartesian robots capturing flying objects. With cumulative citations exceeding 120 across his most recognized works, his research has provided practical and replicable foundations for researchers pursuing embedded autonomy and real-time robotic perception.