M. Brudka

Papers

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About

M. Brudka’s research focuses on intelligent robotics and sensor-based control, with a particular emphasis on using low-cost ultrasonic measurements for high-precision manipulation. Their major contribution lies in developing adaptive neural network systems that restore and interpret noisy ultrasonic data, enabling robots to perform accurate object recognition and grasping tasks that would typically require more expensive sensors. Brudka introduced a novel grasp parameter determination method and an adaptable ultrasonic image restoration technique, demonstrating that intelligent algorithms can compensate for hardware limitations. Their most-cited work, “Intelligent robot control using ultrasonic measurements” (2002), has garnered 15 citations, with a follow-up study in 2003 adding 8 more, establishing a foundation for cost-effective robotic perception. By showing how neural networks can transform crude distance readings into actionable spatial understanding, Brudka’s work has influenced the development of accessible robotic systems for industrial and service applications. Their research remains relevant for engineers seeking to bridge the gap between sensor quality and task performance in autonomous manipulation.