Ramani Kannan
Papers
6
Total Citations
37
H-Index
4
About
Ramani Kannan is a leading researcher at the intersection of numerical optimization and robotics, whose work bridges foundational mathematics with real-world engineering applications. His primary contributions lie in developing novel conjugate gradient (CG) algorithms for solving nonlinear least-squares (NLS) problems, a critical challenge in robotics and control systems. In his highly cited 2023 paper (10 citations), Kannan introduced a modified structured spectral Hestenes-Stiefel method that eliminates the need for a safe guard, improving efficiency in robot arm control. Building on this, his 2024 work (8 citations) proposed two new three-term CG algorithms incorporating second-order curvature information, achieving superior conjugacy and descent properties for NLS problems. Beyond optimization theory, Kannan applies these methods to practical robotics challenges, including stochastic wheel-slip compensation for robot localization (6 citations) and control of self-balancing robots under disturbed surfaces. He also contributes to biomedical engineering, developing an IoT-based smart glove system for cost-effective stroke rehabilitation (7 citations). With a growing citation impact and publications spanning from 2016 to 2024, Kannan’s work exemplifies how advanced mathematical methods can directly enhance robotic systems, from industrial manipulators to assistive healthcare technologies.
Research Focus
Key Achievements
Top Papers
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- 4Stochastic Wheel-Slip Compensation Based Robot Localization and Mapping6 citations · 2016
- 5Control of A Self-Balancing Robot Under a Disturbed Surface4 citations · 2023
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