Sho Onodera
Papers
1
Total Citations
10
H-Index
1
About
Sho Onodera is a roboticist specializing in high-dimensional motion planning and manipulation in complex, cluttered environments. His research focuses on developing computationally efficient path planning algorithms for hyper-redundant manipulators, such as snake-like robots, enabling them to navigate tight, obstacle-filled spaces for inspection and maintenance tasks. Onodera’s most cited work, “Search-based Path Planning for a High Dimensional Manipulator in Cluttered Environments Using Optimization-based Primitives” (2021, 10 citations), introduces a novel hybrid approach that combines heuristic search with optimization-based primitives to solve the challenging 21-degree-of-freedom path planning problem for gas turbine inspection. This contribution is notable for bridging the gap between discrete search and continuous optimization, offering a practical solution for real-world industrial applications. His work has significant implications for automating maintenance in confined, hazardous environments, reducing human risk and downtime. Onodera’s research stands out for its direct application to high-stakes industrial settings, marking him as an emerging leader in manipulation planning for extreme environments.
Research Focus
Key Achievements
Top Papers
- 1