Kazuya Matsuo

About

Kazuya Matsuo’s research lies at the intersection of robotics, human-robot interaction, and intelligent sensing, with a focus on enabling robots to operate safely and effectively in everyday human environments. His major contributions include developing systems for object tracking and recognition using passive RFID tags and embedded sensors, allowing service robots to locate and identify common items in indoor settings. He also pioneered adaptive user-centered design for physical human-robot interaction, particularly in nursing-care contexts, where safety and comfort are paramount. Matsuo’s work on segmenting human manipulation tasks by measuring contact forces on grasped objects provides foundational methods for robots to learn and replicate human dexterity. His most cited paper, “Position tracking and recognition of everyday objects by using sensors embedded in an environment and mounted on mobile robots” (2012, 10 citations), exemplifies his integrated approach to sensor fusion and real-world deployment. Though his citation counts are modest, his research addresses critical challenges in assistive robotics and ambient intelligence, laying groundwork for robots that can collaborate with humans in dynamic, unstructured spaces.

Research Focus

Key Achievements

Top Papers

1. 1
   Position tracking and recognition of everyday objects by using sensors embedded in an environment and mounted on mobile robots

   10 citations · 2012
2. 2
   Adaptive User-Centered Design for Safety and Comfort of Physical Human Nursing – Care Robot Interaction

   6 citations · 2013
3. 3
   Segmentation method of human manipulation task based on measurement of force imposed by a human hand on a grasped object

   6 citations · 2009
4. 4
   Position tracking system for commodities in an indoor environment

   2 citations · 2010

Key Collaborators

Contact & Links