Susheel Praneeth
Papers
1
Total Citations
3
H-Index
1
About
Susheel Praneeth is a researcher focused on the intersection of robotics and reinforcement learning, with a particular emphasis on model-free control strategies for autonomous systems. His most notable contribution is a pioneering work on a universal trajectory tracking controller for mobile robots, which leverages online reinforcement learning to enable adaptive, real-time navigation without requiring a pre-defined system model. This approach addresses a critical challenge in robotics—ensuring robust performance in dynamic, unstructured environments where traditional model-based controllers often fail. While his seminal paper from 2015 has garnered 3 citations, its conceptual impact lies in advancing the practicality of learning-based control for mobile platforms, bridging the gap between theoretical reinforcement learning and real-world robotic applications. Praneeth’s research underscores a commitment to developing scalable, data-driven solutions that enhance the autonomy and versatility of robotic systems. His work serves as a foundation for further exploration into model-free adaptive control, inspiring future innovations in autonomous navigation and intelligent robotics.
Research Focus
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Top Papers
- 1