Soutrik Bandyopadhyay

Indian Institute of Engineering Science and Technology, Shibpur

Papers

Total Citations

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About

Soutrik Bandyopadhyay is a robotics researcher whose work focuses on the control and system identification of non-conventional robotic platforms, particularly continuum robots and wheeled mobile robots. His major contributions lie in addressing the challenge of controlling highly nonlinear, underactuated systems where traditional model-based approaches fall short. In his most-cited work, "Control of Single-Segment Continuum Robots: Reinforcement Learning vs. Neural Network based PID" (2018, 7 citations), Bandyopadhyay pioneered a model-less control strategy, comparing reinforcement learning with neural network-tuned PID controllers to achieve precise motion in these flexible, snake-like robots—critical for applications in medicine, defense, and space exploration. His subsequent research on "System Identification and Control of Wheeled Mobile Robot" (2021, 3 citations) extends this expertise to autonomous ground vehicles, developing robust identification techniques for dynamic modeling. Bandyopadhyay’s work is notable for bridging classical control theory with modern machine learning, offering practical solutions for robots operating in unstructured environments. His research has direct implications for surgical robotics, disaster response, and industrial automation, making him a rising voice in adaptive, data-driven robotic control.