About

Jun Morimoto is a pioneering robotics and computational neuroscience researcher whose work sits at the intersection of machine learning, humanoid robotics, and human-robot interaction. Best known for his foundational contributions to biped locomotion and movement primitives, Morimoto has shaped how robots learn and adapt complex motor behaviors. His early work on learning from demonstration for biped locomotion (400 citations) and minimax differential dynamic programming established robust frameworks for robot control under uncertainty. A central thread throughout his research is the use of Dynamic Movement Primitives (DMPs), with landmark papers on task-specific generalization and Cartesian-space orientation control accumulating over 570 citations combined. Morimoto also co-developed CB, a 50-degree-of-freedom humanoid platform designed to probe the computational principles of the human brain in real-world settings. More recently, he has made significant strides in human-robot collaboration, pioneering EMG-based control systems for exoskeletons and rehabilitation robotics — work that enables assistive devices to adapt intelligently to individual users' muscle activity. With over 2,100 citations across his top papers alone, Morimoto's research continues to influence both the theoretical underpinnings and practical applications of intelligent, human-centered robotics.

Research Focus

Key Achievements

37
H-Index
150
Papers
5,412
Total Citations
36
Avg Citations/Paper
🏆 Most Cited Paper
Learning from demonstration and adaptation of biped locomotion
400 citations · 2004
📈 Most Prolific Year: 2013 (13 Papers)
🤝 Key Collaborators: 140
🏛 Institutions: Japan Science and Technology Agency, Advanced Telecommunications Research Institute International, RIKEN Center for Computational Science, Kyoto Seika University, Oxford Centre for Computational Neuroscience, Nara Institute of Science and Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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