Papers
12
Total Citations
72
H-Index
5
About
Naoya Yamaguchi is a robotics researcher whose work centers on robotic manipulation, sensor integration, and human-robot interaction. His major contributions lie in developing novel grippers and proximity sensing systems that enable robots to adapt to unknown environments for precise object search and grasp. His most-cited paper, "A Gripper for Object Search and Grasp Through Proximity Sensing" (2018, 22 citations), introduces a gripper that uses non-contact sensors to robustly locate and grasp objects, a foundational advance for autonomous manipulation. He further refined this with "Online Acquisition of Close-Range Proximity Sensor Models" (2020, 10 citations), which improves grasping accuracy by calibrating sensors during real-time object interaction. Yamaguchi also explores semantic scene understanding with "Semantic Scene Difference Detection" (2023, 8 citations), leveraging large-scale vision-language models for mobile robots patrolling daily environments. His work on teleoperation interfaces, like the "Miniature Tangible Cube" (2021, 7 citations), enhances dual-arm control by focusing on target-object-oriented user interfaces. With over 60 citations across his top papers, Yamaguchi’s research bridges sensor-driven autonomy and practical robotic applications, making significant strides in adaptive grasping and human-robot collaboration.
Research Focus
Key Achievements
Top Papers
- 1A Gripper for Object Search and Grasp Through Proximity Sensing22 citations · 2018
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