Ming Hao
Papers
6
Total Citations
175
H-Index
6
About
Ming Hao is a leading researcher at the intersection of wearable robotics, human locomotion biomechanics, and 3D perception for autonomous systems. His primary contributions lie in developing novel robotic systems—including supernumerary limbs and wheel-legged robotic appendages—that augment human physical capabilities, particularly for load carriage and demanding tasks like environmental disinfection during COVID-19. Hao’s work on the “Supernumerary Robotic Limbs to Assist Human Walking With Load Carriage” (61 citations) and the “Wheel-Legged Robotic Limb” (23 citations) demonstrates a practical, application-driven approach to reducing metabolic cost and physical burden on users. He has also advanced the understanding of human-robot interaction through studies on energetic response during walking with suspended backpacks (21 citations). Beyond biomechanics, Hao contributes to robotic perception with his “Linked Dynamic Graph CNN” (54 citations), a method for robust point cloud learning that enhances how robots interpret complex environments. His research, supported by numerical simulations and experimental validations, is shaping the future of assistive robotics for both industrial and public health applications.
Research Focus
Key Achievements
Top Papers
- 1Supernumerary Robotic Limbs to Assist Human Walking With Load Carriage61 citations · 2020
- 2
- 3
- 4Energetic Response of Human Walking With Loads Using Suspended Backpacks21 citations · 2021
- 5
- 6