Masahiro Bando

The University of Tokyo

Papers

9

Total Citations

58

H-Index

5

About

Masahiro Bando pushes the boundaries of robot locomotion and manipulation, tackling some of robotics' hardest challenges: dynamic cloth handling, high-jumping monopedal robots, and humanoid mobility in extreme terrain. His work on "Dynamic Cloth Manipulation" (15 citations) introduces a deep predictive model with parametric bias to handle variable stiffness and material changes—a breakthrough for flexible object manipulation. With "RAMIEL" (11 citations), he designed a parallel-wire driven monoped capable of continuous, high jumps, advancing legged robots' ability to navigate 3D environments. Bando's "Simultaneous Planning and Estimation Based on Physics Reasoning" (8 citations) unifies tool use, learning from demonstration, and multi-robot cooperation into a single framework. He also developed the musculoskeletal wheeled robot Musashi-W (6 citations), bridging the gap between flexible humanoid bodies and real-world tasks. His work on rappelling humanoids (3 citations) and steep-slope walking with ropes (6 citations) expands robots' vertical mobility. Most recently, his kangaroo-inspired robot design (2 citations) combines powerful legs with an articulated soft tail. With over 50 total citations and a consistent focus on hardware-software co-design, Bando is shaping the future of robots that can jump, climb, manipulate, and adapt to unstructured environments.

Research Focus

Key Achievements

5
H-Index
9
Papers
58
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
Dynamic Cloth Manipulation Considering Variable Stiffness and Material Change Using Deep Predictive Model With Parametric Bias
15 citations · 2022
📈 Most Prolific Year: 2022 (3 Papers)
🤝 Key Collaborators: 21
🏛 Institutions: The University of Tokyo

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago