N. Nikseresht

Iran University of Science and Technology

Papers

Total Citations

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About

N. Nikseresht is a robotics researcher whose work centers on the dynamic modeling, simulation, and control of advanced wheel-legged robotic systems. Their primary research areas include hybrid locomotion, nonlinear dynamics, and adaptive control, with a particular focus on addressing the persistent challenge of wheel slippage in rough terrain. A key contribution is the development of a vision-based dynamic model using the Gibbs–Appell formulation, which accurately accounts for both kinematic and dynamic slippage in wheeled-legged robots (WLRs). This work, published in 2024, provides a more precise foundation for motion planning and control. Nikseresht has also advanced adaptive control strategies, notably proposing an adaptive MIMO PID control framework for wheel-leg manipulators that leverages deep reinforcement learning to tune gains in real time, effectively handling unknown dynamics and external disturbances. Their foundational paper on modeling and simulation of wheel-leg robots (2022) has garnered 4 citations, while their reinforcement learning-based PID approach (2023) has also achieved 4 citations, demonstrating early impact in this niche field. Collectively, Nikseresht’s research pushes the boundaries of autonomous locomotion for hybrid robots operating in unstructured environments.