Andrea Pergolini
Papers
2
Total Citations
9
H-Index
2
About
Andrea Pergolini is a researcher advancing the field of wearable robotics and human locomotion assistance. His work centers on developing intelligent control strategies for lower-limb exoskeletons, with a particular focus on enabling seamless, real-time adaptation to diverse daily-life environments. Pergolini’s major contributions include pioneering the use of Adaptive Dynamic Movement Primitives for continuous gait phase estimation across multiple locomotion modes—a critical step for synchronizing robotic assistance with a user’s natural movements. His 2023 paper on this topic has already garnered 5 citations, reflecting its timely impact. In related work (2022, 4 citations), he experimentally validated a control strategy inspired by simplified motor primitives from the human neuromuscular system, demonstrating how bio-inspired approaches can handle ecological, non-steady walking conditions. By tackling the challenge of transitioning between rhythmic and non-rhythmic tasks, Pergolini is helping bridge the gap between laboratory-tested exoskeletons and real-world usability. His research is particularly relevant for students and engineers seeking to understand how adaptive, nature-inspired algorithms can make wearable robots more intuitive and responsive to human intent.
Research Focus
Key Achievements
Top Papers
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