Saroj Prasad Chhatoi

Piaggio (Italy), Laboratoire d'Analyse et d'Architecture des Systèmes

Papers

Total Citations

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About

Saroj Prasad Chhatoi is a leading researcher in robotics, specializing in optimal control and model predictive control (MPC) for complex robotic systems. His work bridges the gap between theoretical control methods and practical deployment, particularly for legged and soft robots. Chhatoi’s major contribution includes the development of "Inverse-Dynamics MPC via Nullspace Resolution," a 2023 paper with 41 citations that introduces a novel approach to leverage inverse dynamics in MPC. This method offers numerical benefits like coarse optimization and high convergence rates, enabling more efficient and stable control for legged robots. Additionally, his 2023 work on "Optimal Control for Articulated Soft Robots" (9 citations) pioneers the use of differential dynamic programming (DDP) to unlock the full potential of soft robots, which are inherently safer for human interaction. By addressing the critical challenge of effectively controlling these compliant systems, Chhatoi’s research is paving the way for safer, more agile robots in real-world applications. His contributions are highly influential for students and researchers aiming to advance robotic autonomy and human-robot interaction.