Shunhao Oh

Papers

Total Citations

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About

Shunhao Oh is a researcher whose work has advanced the field of motion path planning, particularly in robotics and video game AI. His key research area focuses on developing efficient algorithms for navigating dynamic 2D open spaces, where environments are represented as grids of blocked and unblocked cells. Oh’s most notable contribution is the **Strict Theta\*** algorithm, a refinement of the Basic Theta\* method. While Basic Theta\* produces near-optimal paths with running times close to A\* on 8-directional grids, Strict Theta\* improves upon this by generating shorter, tauter paths that more closely approximate true shortest paths. This work, published in 2016, has garnered 8 citations and is recognized for addressing a critical limitation in any-angle path planning: the tendency of previous algorithms to produce unnecessarily long or jagged routes. Oh’s contributions are particularly valuable for real-time applications, such as autonomous robot navigation and character movement in video games, where both path quality and computational efficiency are paramount. His research continues to influence the development of smarter, more natural-looking movement in constrained grid-based environments.