Masahiko Osawa
Papers
5
Total Citations
50
H-Index
4
About
Masahiko Osawa is a leading researcher in human-robot interaction, specializing in semi-autonomous telepresence systems and interactive machine learning. His work addresses the critical challenge of designing robots that can intelligently balance autonomous behavior with human control, ensuring seamless collaboration between local users and remote operators. Osawa’s major contributions include developing adaptive frameworks that use inhibition and disinhibition mechanisms to automatically switch between remote and autonomous operation, reducing operator frustration. He pioneered the use of episodic control and online learning to enable robots to adapt to user preferences and avoid discomfort stimuli in real time. His most cited work, “Autonomous Self-Explanation of Behavior for Interactive Reinforcement Learning Agents” (29 citations), tackles the “black box” problem in machine learning by making agent policies understandable to human collaborators. Osawa also created a handheld telepresence test bed with binaural audio and head-mounted displays to study user comfort. His research has been published in top venues including ACM/IEEE conferences, and he is recognized for advancing the theory and practice of shared autonomy—a cornerstone for future collaborative robotics in healthcare, manufacturing, and remote assistance.
Research Focus
Key Achievements
Top Papers
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- 5Adaptive Semi-autonomous Agents via Episodic Control3 citations · 2018