Vladimir Zaborovsky

Peter the Great St. Petersburg Polytechnic University

Papers

Total Citations

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About

Vladimir Zaborovsky is a researcher whose work sits at the intersection of robotics, artificial intelligence, and network-centric systems. His research focuses primarily on anomaly detection in multi-robot systems and cyber-physical approaches to robot control, addressing the growing challenge of maintaining reliability and security in complex, distributed robotic environments. Among his most recognized contributions is a 2017 paper introducing a Siamese autoencoder architecture specifically designed for anomaly detection in multi-robot systems, which has garnered 17 citations. This innovative approach employs two identical autoencoders with shared encoder weights to reduce the dimensionality of sensor data while preserving critical distance relationships — enabling more effective preprocessing and detection of irregularities in robot behavior. The work represents a meaningful bridge between deep learning techniques and practical robotics applications. His earlier 2014 contribution on cyber-physical approaches to network-centric robot control further demonstrates his sustained interest in integrating computational intelligence with physical robotic systems, exploring how networked architectures can enhance control and coordination. Together, Zaborovsky's publications reflect a coherent research vision: applying sophisticated machine learning and systems-level thinking to make autonomous and multi-robot systems more robust, intelligent, and resilient in real-world deployments.