Papers
7
Total Citations
90
H-Index
5
About
Krishanu Nath is an emerging robotics and control systems researcher whose work sits at the intersection of robust control theory, networked systems, and autonomous mobile robotics. His research primarily focuses on developing advanced sliding mode control (SMC) strategies — including integral and super-twisting variants — for wheeled mobile robots and robotic manipulators operating in uncertain, networked environments. A defining theme across his publications is the event-triggered control paradigm, which addresses the practical challenge of reducing communication and computational overhead without sacrificing tracking performance, a critical concern for wireless robotic systems. Nath's most influential work, "Event-Triggered Sliding-Mode Control of Two Wheeled Mobile Robot" (2021, 40 citations), demonstrated the experimental viability of this approach, lending credibility to theoretical frameworks through real-world validation. His subsequent research introduced neural network-based adaptive controllers using radial basis function architectures and concurrent learning, earning 27 citations and showcasing his ability to blend machine learning with classical robust control. His contributions to path planning algorithms further reflect his broad systems-level perspective on autonomous robotics. Collectively, his growing citation record signals a meaningful contribution to resource-efficient, resilient robot control — areas of increasing relevance as autonomous systems become more pervasive.
Research Focus
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