Michael C.F. Bazzocchi
Clarkson University, University of Toronto, Astronautics Corporation of America
Papers
6
Total Citations
91
H-Index
4
About
Michael C.F. Bazzocchi is a pioneering researcher at the intersection of rehabilitation robotics and space-based energy systems. His primary contributions lie in developing adaptive, patient-specific control strategies for lower-body exoskeletons using model-free deep reinforcement learning—work that directly addresses the challenge of providing "assistance-as-needed" to enhance motor learning during post-stroke gait rehabilitation. His most influential paper (41 citations) introduces a reinforcement learning framework that personalizes exoskeleton gait patterns in real time, while his end-to-end control approach (27 citations) eliminates the need for complex system models. More recently, Bazzocchi has expanded into space-based solar power, optimizing the simultaneous orbit and attitude control of planar arrays for wireless power transmission. His work on Molniya orbit attitude trajectory design and shape memory alloy actuated robotic arms for aerial manipulation demonstrates a rare versatility across domains. With over 90 total citations and a growing portfolio that bridges terrestrial rehabilitation and extraterrestrial energy infrastructure, Bazzocchi exemplifies how robotic control principles can be translated across radically different applications—from restoring human mobility to enabling sustainable space power.
Research Focus
Key Achievements
Top Papers
- 1
- 2End-to-End Deep Reinforcement Learning for Exoskeleton Control27 citations · 2020
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- 5
- 6A shape memory alloy actuated robotic arm for aerial manipulation1 citations · 2025