Hiraku Yagi

Papers

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About

Hiraku Yagi is a roboticist advancing tactile perception for autonomous manipulation, with a focus on enabling robots to estimate object pose without heavy reliance on visual sensors. His key research areas include soft tactile sensing, state estimation, and particle filter algorithms for robotics. Yagi’s major contribution is the development of the **Continuous Manifold Particle Filter (C-MPF)**, an extension of the traditional Manifold Particle Filter that can handle continuous, multidimensional observations from soft tactile sensors. This innovation allows robots to iteratively contact objects and infer their pose with high accuracy, even in visually occluded or poorly lit environments. His work, published in 2023 and 2024, has already garnered early citations (3 and 2, respectively), signaling growing interest from the manipulation and sensor communities. By reducing dependence on cameras, Yagi’s approach promises more robust and cost-effective robotic systems for tasks like assembly, grasping, and inspection. His research stands out for its elegant fusion of probabilistic filtering with real-world tactile data, offering a practical path toward dexterous, sensor-rich robots that can operate in challenging conditions.