Papers
8
Total Citations
47
H-Index
4
About
Ansi Peng is a robotics researcher whose work spans rehabilitation engineering, mobile robot design, and human-robot interaction. Over more than a decade of research, Peng has made significant contributions to two primary domains: wearable exoskeleton systems for medical rehabilitation and adaptive mobile robot platforms. Peng's most influential work focuses on lower limb exoskeleton robots designed to assist elderly individuals and stroke patients with walking dysfunction. A 2013 paper on flexible exoskeleton design (13 citations) laid foundational groundwork in this area, while more recent research from 2024 advances the field by generating individualized gait trajectories clinically validated for stroke rehabilitation (10 citations), addressing the critical challenge of personalizing recovery pathways. Complementary work on Extended Kalman Filter-based state estimation further refines exoskeleton safety and precision. Beyond rehabilitation, Peng has demonstrated versatility through innovations in mobile robotics, including a wheel-track transformation robot capable of navigating both smooth and rugged terrains (7 citations), a tumbler-inspired wheeled robot with self-stabilizing characteristics, and autonomous wall-following navigation strategies. A 2018 contribution exploring compliant manipulation learning from force demonstrations (6 citations) reflects Peng's broader interest in making robots adaptable to unstructured, human-centered environments. Collectively, Peng's portfolio reflects a consistent commitment to building robots that serve human needs across healthcare and real-world operational contexts.
Research Focus
Key Achievements
Top Papers
- 1Flexible design of a wearable lower limb exoskeleton robot13 citations · 2013
- 2
- 3On study of a wheel-track transformation robot7 citations · 2015
- 4Learning Compliant Manipulation Tasks from Force Demonstrations6 citations · 2018
- 5On a novel wheeled robot with tumbler characteristics4 citations · 2011
- 6A wall-following strategy for mobile robots based on self-convergence3 citations · 2011
- 7
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