Rengarajan Amirtharajan

About

Rengarajan Amirtharajan is a leading researcher at the intersection of robotics, artificial intelligence, and bio-inspired systems, with a primary focus on the control and modeling of robotic fish. His work centers on developing intelligent, data-driven controllers that enable biomimetic underwater vehicles to achieve precise speed tracking and agile locomotion. Amirtharajan’s major contributions include pioneering the use of deep reinforcement learning (DRL) for real-time speed control in two-link surface-swimming robotic fish, as demonstrated in his highly cited 2022 paper (23 citations). He further advanced this field by implementing a real-time DRL controller validated through data-assisted hydrodynamic modeling, incorporating Newtonian dynamics and Lighthill’s kinematic model to account for external unsteady reactions. His 2023 work on genetic algorithm-optimized grey-box modeling and fuzzy logic controllers for tail-actuated robotic fish showcases his versatility in combining evolutionary optimization with soft computing. With over 35 total citations, Amirtharajan’s research is pivotal for autonomous underwater vehicles, offering robust, adaptive control solutions that bridge theoretical hydrodynamics and practical robotics. His achievements highlight a commitment to pushing the boundaries of bio-inspired engineering and intelligent control systems.

Research Focus

Key Achievements

Top Papers

1. 1
   Design of Deep Reinforcement Learning Controller Through Data-assisted Model for Robotic Fish Speed Tracking

   23 citations · 2022
2. 2
   Real-time implementation of deep reinforcement learning controller for speed tracking of robotic fish through data-assisted modeling

   10 citations · 2023
3. 3
   Genetic Algorithm Optimized Grey-Box Modelling and Fuzzy Logic Controller for Tail-Actuated Robotic Fish

   2 citations · 2023

Key Collaborators

Contact & Links