Max Robotics — Global Service Robot Directory + US Certification

About

Sohrab Khanmohammadi is a robotics and intelligent systems researcher whose work spans trajectory prediction, path planning, and advanced robot control. With a career stretching from foundational neural network applications in the 1990s to cutting-edge exoskeleton control in the 2020s, his contributions reflect a sustained commitment to making robots smarter and more adaptive in real-world environments. Khanmohammadi's most recognized work applies probabilistic and fuzzy methods to complex robotics challenges. His 2011 paper on Gaussian Process-based trajectory prediction (28 citations) addressed a critical gap in online learning from small datasets, offering a practical alternative to conventional approaches like MLP and ANFIS. His 2021 study on model-free adaptive iterative learning control for exoskeleton robots (26 citations) introduced a data-driven framework for managing multi-degree-of-freedom systems under real-world disturbances. His 2017 research on soft robotics catheter control (25 citations) further demonstrated his versatility across medical and industrial applications. Throughout his career, Khanmohammadi has consistently pioneered hybrid intelligent methods — blending fuzzy logic, neural networks, and adaptive control — to solve dynamic, uncertain environments that challenge traditional robotics. His body of work offers valuable foundational reading for researchers interested in intelligent control systems and autonomous robot navigation.