Taiki Onuma

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About

Taiki Onuma is a leading researcher in autonomous vehicle navigation and path planning, with a focus on bridging the gap between 2D and 3D environments. His most cited work, "Two-Lane Path Planning of Autonomous Vehicles in 2.5D Environments" (2019, 17 citations), introduces a novel approach that extends collision-free 2D path-planning techniques into 2.5D spaces by mapping paths from parameter space onto complex terrains. This contribution is critical for enabling autonomous vehicles to navigate safely in semi-structured, non-flat environments, such as uneven roads or off-road settings. Onuma’s research directly addresses the challenge of maintaining lane discipline while adapting to elevation changes, a key step toward real-world deployment of self-driving systems. His work has garnered attention for its practical implications in robotics and intelligent transportation, with citations reflecting its influence on subsequent studies in multi-lane planning and terrain-aware navigation. By systematically advancing from 2D to 2.5D path planning, Onuma has established himself as a key innovator in the field, providing foundational algorithms that continue to shape how autonomous vehicles perceive and move through complex landscapes.