Max Robotics — Global Service Robot Directory + US Certification

About

Noritsugu Miyazawa is a robotics researcher focused on advancing tactile sensing for object manipulation, particularly in environments where vision is unreliable. His core research areas include state estimation of deformable objects, object pose estimation using soft tactile sensors, and optimal action selection for robotic manipulation. Miyazawa’s major contributions center on extending the Manifold Particle Filter (MPF) to handle continuous, multidimensional tactile observations—a method he calls C-MPF—enabling robots to estimate object poses through iterative contacts without heavy reliance on visual sensors. His work has practical applications in industrial settings, such as estimating the aperture of bags or containers to select objects, using force-torque sensors and information gain-based action selection. With several papers published in 2023-2024, his most-cited work, “Optimal action selection to estimate the aperture of bag by force-torque sensor” (4 citations), demonstrates his ability to integrate probabilistic filtering with real-world robotic tasks. Miyazawa’s research is notable for tackling the challenge of occlusion and unreliable vision, offering robust tactile solutions that enhance robotic autonomy in production and logistics.