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About

Jeonghoon Kwak is a robotics researcher whose work focuses on autonomous navigation, motor primitive generation, and perception systems for mobile robots operating in structured and unstructured environments. His key contributions span UAV autonomy, agricultural robotics, and cleaning robot automation. Kwak’s most cited paper, “Graph-based motor primitive generation framework” (2015, 9 citations), introduces a novel approach for defining UAV motor primitives to enable autonomous flight, addressing a critical challenge in drone applications like delivery and surveillance. He has also advanced localization and control in agricultural settings, as seen in “GPS Error Filtering using Continuity of Path for Autonomous Mobile Robot in Orchard Environment” (2024, 5 citations), which improves path accuracy for orchard navigation. His work on object recognition, “Variance Optimization Based on Guided Anchor Siamese Network for Target-of-interest Object Recognition in Autonomous Mobile Robots” (2023, 4 citations), enhances robot perception in dynamic settings. Additionally, Kwak has developed lateral control methods for cleaning robots (2024, 2 citations) and extended marker sensing range using tilt cameras (2023, 2 citations), demonstrating his versatility in sensor integration and control. With a growing citation record, Kwak’s research is shaping practical autonomous systems for agriculture, logistics, and service robotics.