S Selvakumaran
Papers
2
Total Citations
7
H-Index
2
About
S. Selvakumaran is a robotics researcher specializing in locomotion, reinforcement learning, and reconfigurable robotic systems. Their work addresses two critical challenges in modern robotics: enabling humanoid robots to learn adaptive walking behaviors and designing versatile robots for infrastructure inspection. In their highly cited 2023 paper on biped robot gait design, Selvakumaran pioneered the use of an Actor-Critic reinforcement learning method, demonstrating that learning-based approaches can outperform hand-engineered walking controllers in complex, unstructured environments. This work has garnered 5 citations and provides a foundation for more robust robot-assisted mobility solutions. Additionally, Selvakumaran contributed to the design of a self-reconfigurable robot capable of rolling, crawling, and climbing, specifically tailored for false ceiling inspection tasks. This innovation, published in 2023, showcases their ability to merge mechanical adaptability with practical application, addressing real-world maintenance needs. Through these contributions, Selvakumaran advances the frontier of autonomous robotics, bridging the gap between theoretical learning algorithms and deployable, multifunctional robots.
Research Focus
Key Achievements
Top Papers
- 1
- 2