Kostyantyn Kolesnyk

Papers

Total Citations

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About

Kostyantyn Kolesnyk is a robotics researcher whose work bridges embedded systems, computer vision, and intelligent control for mobile and humanoid robots. His most cited paper, "Object Recognition for a Humanoid Robot Based on a Microcontroller" (13 citations), tackles the challenge of implementing real-time object recognition on resource-constrained hardware by leveraging the ESP32-Cam module—a contribution that demonstrates how low-cost microcontrollers can enable sophisticated robotic perception. Kolesnyk’s earlier work on managing robot kinematics with Arduino and Unity (5 citations) provides a practical framework for controlling robotic arms through intuitive software interfaces, while his research on MEMS accelerometers in hexapod control (4 citations) applies machine learning to classify robot states in real time, advancing autonomous locomotion. His recent study on mobile robot navigation using ultrasonic sensors (4 citations) further underscores his focus on accessible, sensor-driven navigation systems. Across these projects, Kolesnyk consistently emphasizes cost-effective, microcontroller-based solutions that make robotics more deployable in educational and research settings. His work is particularly notable for integrating modern development tools like Unity and machine learning into traditional robotic control, offering students and researchers a clear pathway from theory to functional, low-cost robotic systems.