Shou Minoura
Papers
1
Total Citations
2
H-Index
1
About
Shou Minoura is a robotics researcher whose work centers on advancing dexterous manipulation in hand/arm robotic systems, with a particular focus on integrating vision and tactile feedback for precise object handling. His key contributions lie in developing multi-fingered robot hands equipped with multi-axis force/torque sensors, enabling robots to perform pick-up and placement motions that are both stable and gentle—avoiding drops while preventing damage to objects. This research addresses a critical challenge in robotics: achieving human-like sensitivity and control during manipulation tasks. Though his most-cited paper, "Pick-Up Motion Based on Vision and Tactile Information in Hand/Arm Robot" (2016), has garnered modest attention with 2 citations, it represents foundational work in sensorimotor integration for robotic grasping. Minoura’s efforts contribute to broader applications in industrial automation, assistive robotics, and human-robot interaction, where reliable and adaptive manipulation is essential. His work underscores the importance of multimodal sensing—combining visual data with tactile feedback—to enhance robotic autonomy and safety in real-world environments.
Research Focus
Key Achievements
Top Papers
- 1Pick-Up Motion Based on Vision and Tactile Information in Hand/Arm Robot2 citations · 2016