Papers
26
Total Citations
585
H-Index
11
About
Vikas Panwar is a distinguished robotics and control systems researcher whose work has significantly advanced the field of intelligent control for robot manipulators. His research spans neural network-based control, hybrid force/position control, adaptive control systems, and autonomous robot navigation — areas in which he has built a remarkably cohesive and impactful body of work. Panwar's most celebrated contributions lie in applying neural network architectures to solve complex manipulation challenges. His 2011 papers on hybrid force/position control and cooperative multi-robot manipulation — garnering 93 and 79 citations respectively — established him as a leading voice in intelligent robotic control. His work on kinematically redundant manipulators and RBF neural network-based tracking controllers further demonstrated his ability to tackle real-world robotic constraints with mathematical rigor. Beyond manipulators, Panwar extended his expertise to space robotics, adaptive neuro-fuzzy systems, wavelet neural networks with H∞ performance guarantees, and PSO-optimized navigation of wheeled robots in obstacle-rich environments. His consistent productivity across more than a decade, with cumulative citations exceeding 480, reflects both the depth and durability of his contributions. Students exploring intelligent robotics, adaptive control, or autonomous systems will find Panwar's work an essential and richly rewarding reference point.
Research Focus
Key Achievements
Top Papers
- 1Neural network based hybrid force/position control for robot manipulators93 citations · 2011
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