Shohei Taniguchi
Papers
3
Total Citations
42
H-Index
2
About
Shohei Taniguchi is a robotics researcher whose work spans robot manipulation, perception, and autonomous systems for real-world applications. His research is primarily focused on solving fundamental challenges in robotic grasping and manipulation, with a particular emphasis on making robots more adaptable and intelligent in unstructured environments. Taniguchi's most recognized contribution is his 2020 work on contact-based in-hand pose estimation, which garnered 27 citations. This research addressed a critical bottleneck in industrial assembly robotics — accurately knowing the position of a grasped object without relying on rigid, task-specific jigs. By applying Bayesian state estimation and particle filtering, his approach significantly enhanced flexibility in automated assembly pipelines, offering a practical alternative to traditional fixturing methods. Beyond industrial settings, Taniguchi has also contributed to household robotics research. His work on the World Robot Challenge 2020 Partner Robot task demonstrates his breadth, tackling real-world room tidying using mobile manipulators through data-driven methodologies — addressing challenges such as environmental variability and safe human-robot coexistence. With a growing citation record and participation in prestigious international robotics competitions, Taniguchi represents an emerging voice in intelligent manipulation and autonomous robot deployment research.
Research Focus
Key Achievements
Top Papers
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