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About

Tri Kuntoro Priyambodo is an Indonesian robotics researcher whose work centers on mobile robot navigation, autonomous path planning, and vision-based sensing systems. His research consistently addresses the challenge of enabling robots to navigate complex, dynamic environments safely and efficiently. Priyambodo's most recognized contribution is his comprehensive review of vision-based robot navigation methods (2015, 8 citations), which has served as a foundational reference for researchers entering the field. Building on this, he developed the innovative Grid-Edge-Depth Map technique — a stereo camera-based obstacle mapping approach that translates visual data into actionable 2D spatial representations, enabling wheeled robots to identify and avoid obstacles in real time. His work on path planning algorithms has been particularly impactful, with multiple studies examining ant colony optimization and comparative algorithm analyses in dynamic environments. He has also contributed practically to the field through a web-controlled mobile robot prototype leveraging TCP/IP wireless networks, demonstrating applied expertise beyond theoretical research. Across his published work, Priyambodo bridges algorithm development, computer vision, and practical robotics engineering. With a growing citation record and contributions spanning humanoid robots, stereo vision mapping, and autonomous navigation, his research offers valuable insights for students and engineers working at the intersection of artificial intelligence and robotic systems.