Kotaro Shibata
Papers
2
Total Citations
48
H-Index
2
About
Kotaro Shibata is a leading researcher in robotic tactile perception and active sensing, whose work addresses a critical challenge in real-world manipulation: how robots can efficiently and accurately estimate the shape of unknown objects through touch. His primary research areas include active tactile exploration, uncertainty-driven sensing, and sensorimotor control for grasping. Shibata’s major contribution lies in developing algorithms that treat tactile exploration as a sequential decision-making problem, where the robot actively selects touch points to minimize shape estimation uncertainty while accounting for the travel cost of moving its sensor. This approach, detailed in his most cited paper (2017, 35 citations), enables fast and reliable shape reconstruction even when vision is noisy or occluded. His earlier work (2016, 13 citations) laid the foundation by introducing active touch point selection strategies that balance information gain with physical effort. Shibata’s research has significant implications for autonomous robots operating in cluttered or poorly lit environments, where tactile feedback is essential for safe and precise interaction. His contributions are widely recognized in the robotics community, and his methods continue to influence the design of intelligent, touch-guided manipulation systems.
Research Focus
Key Achievements
Top Papers
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