Masoud Shariat Panahi
Papers
6
Total Citations
69
H-Index
4
About
Masoud Shariat Panahi is a robotics and intelligent systems researcher whose work bridges reinforcement learning, motion planning, and control of mobile and legged robots. His most significant contributions center on applying eXtended Classifier Systems (XCS)—a form of learning classifier system—to solve complex motion planning and stability control problems. Notably, his 2016 paper on XCS-based reinforcement learning for spherical mobile robot motion planning has garnered 29 citations, establishing a foundation for learning-based navigation in non-wheeled platforms. He further advanced the field by addressing the optimal motion planning of mobile manipulators, minimizing platform movements while achieving end-effector positioning—a practical challenge in industrial automation. His work on the XCSRR controller for biped robot stability control (8 citations) introduced a real-time, real-value adaptation of XCS, enabling robust balance in dynamic environments. Beyond robotics, Panahi has explored sensor technology, co-authoring a 2020 paper on flexible temperature sensors using fluorinated graphene. His research consistently demonstrates a commitment to integrating machine learning with mechanical systems, offering efficient, adaptive solutions for autonomous robots operating in hazardous or unstructured environments.
Research Focus
Key Achievements
Top Papers
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- 4Motion planning of a spherical robot using eXtended Classifier Systems5 citations · 2013
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- 6Flexible Temperature Sensor based on Fluorinated Graphene2 citations · 2020