Masato Horikawa
Papers
1
Total Citations
2
H-Index
1
About
Masato Horikawa is a robotics researcher whose work centers on human-robot collaboration, semi-autonomous systems, and adaptive control. His most notable contribution is the design of a 3-D operation support system that leverages Gaussian Process Regression to enable variable autonomy in robotic reaching tasks. This system facilitates overlapping interaction, where a human operator and an automatic controller dynamically share control over a robot manipulator, allowing for flexible and intuitive collaboration in complex manual tasks. Horikawa’s research addresses critical challenges in shared autonomy, aiming to enhance efficiency and safety in human-robot teams. While his work is still emerging—his 2023 paper has garnered 2 citations—it reflects a growing interest in data-driven approaches to robot control and operator support. His contributions are particularly relevant for applications in manufacturing, assistive robotics, and teleoperation, where seamless human-robot coordination is essential. As a researcher focused on the intersection of machine learning and robotics, Horikawa is laying groundwork for more intelligent and responsive collaborative systems.
Research Focus
Key Achievements
Top Papers
- 1