Papers
26
Total Citations
237
H-Index
10
About
Takashi Yoshioka is a multidisciplinary robotics researcher whose work spans industrial robot control, autonomous navigation, haptic perception, and medical robotics. He is perhaps best known for his foundational contributions to sensorless force control in industrial robots, developing innovative methods that enable precise contact detection and smooth transitions between position and force control without the need for dedicated force sensors. His 2016 paper on spring-ratio-based force control, his most cited work with 33 citations, exemplifies his ability to translate complex mechanical modeling into practical industrial solutions. Complementing this, his Kalman-filter-based instantaneous state observer significantly advanced robust motion control against dynamic torque disturbances. Yoshioka's early career produced influential work in sensor-based mobile robot navigation, including deadlock-free path-planning algorithms capable of operating under real-world uncertainties such as dead reckoning errors. He also contributed to our understanding of tactile texture perception through probes, bridging human sensory psychology with robotic sensing design. Perhaps most strikingly, his involvement in the first robotic renal autotransplantation performed outside North America demonstrates a remarkable breadth, extending his robotics expertise into cutting-edge surgical applications. Across these diverse fields, Yoshioka has consistently pursued the challenge of making robots more responsive, precise, and adaptable to complex environments.
Research Focus
Key Achievements
Top Papers
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- 2Factors Involved in Tactile Texture Perception Through Probes20 citations · 2009
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- 4Robotic Renal Autotransplantation: First Case Outside of North America.16 citations · 2017
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