Papers
4
Total Citations
128
H-Index
3
About
Woo Jin Jang is a robotics researcher whose work focuses on advancing robot path planning and autonomous navigation in constrained environments. His most significant contribution is the development of an improved RRT-Connect algorithm that leverages the triangular inequality theorem for efficient rewiring, dramatically reducing planning time while bringing paths closer to optimality. This work, published in 2021, has garnered 119 citations, underscoring its impact on the field of motion planning. Jang’s research also extends to practical robotic applications, including the design and control of duct cleaning robots capable of autonomously navigating complex L-shaped and T-shaped duct sections. His system enables real-time position tracking and self-driving in confined spaces, addressing critical challenges in infrastructure maintenance. Through these contributions, Jang bridges theoretical advances in sampling-based planning algorithms with real-world robotic systems, demonstrating a commitment to both algorithmic innovation and applied robotics.
Research Focus
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Top Papers
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