Deepak Narang

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About

Deepak Narang is a leading researcher in mobile robotics and autonomous navigation, with a primary focus on path-following control for nonholonomic wheeled systems. His most impactful work, "Path Following of Wheeled Mobile Robots Using Online-Optimization-Based Guidance Vector Field" (2021, 37 citations), introduces a novel approach that represents path-following tasks through guidance vector fields (GVF). Narang’s key contribution lies in developing an online optimization procedure to estimate path error in real time, significantly enhancing the accuracy and adaptability of robot navigation under nonholonomic constraints. By employing matrix-measure-based contraction analysis, he provides rigorous stability guarantees for these systems, bridging the gap between theoretical control theory and practical implementation. This work has been widely cited by researchers in robotics and control engineering, underscoring its influence on advancing autonomous vehicle guidance. Narang’s research addresses critical challenges in mobile robot motion planning, offering efficient solutions for applications ranging from warehouse automation to field robotics. His achievements demonstrate a deep commitment to creating robust, real-time navigation frameworks that push the boundaries of autonomous system performance.