Papers
7
Total Citations
89
H-Index
5
About
Monika Harant is a robotics and biomechanics researcher whose work spans two complementary domains: humanoid robot locomotion and exoskeleton design optimization. Her research is distinguished by the innovative integration of optimal control, movement primitives, and machine learning to solve complex motion generation challenges. In humanoid robotics, Harant made significant contributions through the COCoMoPL framework, which combines optimal control with learned movement primitives to generate sophisticated walking motions and successfully transfer them to real platforms such as HRP-2 and REEM-C. These foundational papers, accumulating 29 and 22 citations respectively, established her as a key contributor to practical humanoid locomotion research. Her development of the I3SA benchmark further advanced the field by providing standardized tools for evaluating walking performance. Harant's parallel research thread addresses occupational biomechanics, particularly the design of passive spinal exoskeletons to reduce low-back injury risk in industrial settings. By coupling multibody dynamics with subject-specific modeling and optimal control, she has helped bridge the gap between theoretical exoskeleton design and real-world user needs, work recognized across multiple publications totaling over 25 citations in this domain alone. Her research exemplifies rigorous computational approaches applied to tangible human-centered challenges.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6
- 7