Manju Rani

National Institute of Technology Kurukshetra

Papers

Total Citations

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About

Manju Rani is a robotics and control systems researcher whose work centers on the dynamics and intelligent control of robotic manipulators, with a particular focus on redundant and mobile systems. Her research addresses some of the most challenging problems in modern robotics, including trajectory tracking, force/motion control, and the incorporation of actuator dynamics into control frameworks — factors often overlooked in simplified models but critical for real-world performance. Among her notable contributions is her development of hybrid and intelligent control schemes that combine model-based controllers with Radial Basis Function (RBF) neural networks and adaptive bounding techniques. This approach, explored in her 2016 and 2018 works, enables robust trajectory tracking even in the presence of system uncertainties, pushing the boundaries of what autonomous robotic arms can achieve. Her 2019 paper extends this framework to constrained mobile manipulators, a particularly complex class of systems with broad applications in industrial automation and service robotics. With citations accumulating across her publications — including 8 citations for her force/motion control study and 7 for her intelligent tracking work — Rani's research is gaining recognition within the robotics community. Her interdisciplinary approach, bridging neural computation and classical control theory, positions her as a meaningful contributor to next-generation intelligent robotic systems.