About

Masaki Murooka is a robotics researcher whose work spans humanoid robot motion planning, whole-body manipulation, and model predictive control for legged systems. His research addresses some of the most challenging problems in robotics: enabling humanoid robots to physically interact with their environments in complex, real-world scenarios. Murooka's most influential contribution is his work on model predictive control of legged and humanoid robots (2023, 76 citations), which surveys and advances algorithmic frameworks that have reshaped how robots plan and execute dynamic motion. His pioneering research on whole-body pushing manipulation (2015, 56 citations) demonstrated that humanoid robots could leverage their entire body — not just their hands — to move large, heavy objects, fundamentally broadening the scope of robotic manipulation. His loco-manipulation planning research (2021, 34 citations) further established efficient methods for humanoid robots to autonomously transport objects while navigating complex environments. Beyond humanoids, Murooka has contributed to aerial robotics, developing transformable multilink aerial robots capable of sophisticated regrasping maneuvers (2020, 34 citations). His participation in the prestigious DARPA Robotics Challenge Finals as part of Team NEDO-JSK (2015, 26 citations) underscores his commitment to real-world disaster-response robotics. With over 350 cumulative citations, Murooka stands as a significant voice in advancing autonomous, physically capable robotic systems.

Research Focus

Key Achievements

14
H-Index
44
Papers
621
Total Citations
14
Avg Citations/Paper
🏆 Most Cited Paper
Model predictive control of legged and humanoid robots: models and algorithms
76 citations · 2023
📈 Most Prolific Year: 2020 (7 Papers)
🤝 Key Collaborators: 69
🏛 Institutions: National Institute of Advanced Industrial Science and Technology, The University of Tokyo, Robotics Research (United States)

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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