Sanketh Datla
Papers
1
Total Citations
2
H-Index
1
About
Sanketh Datla is a researcher whose work sits at the intersection of mobile robotics and artificial intelligence, with a particular focus on real-time autonomous navigation. His most-cited paper, "Novel design for real time path tracking with computer vision using neural networks," addresses one of the most persistent challenges in robotics: enabling a machine to accurately localize and map itself within an unstructured, unknown environment. Datla’s contribution lies in his novel integration of computer vision with neural networks to achieve precise, real-time path tracking—a critical capability for autonomous systems operating in dynamic settings. While his citation count is modest, the foundational nature of his work on simultaneous localization and mapping (SLAM) and neural-network-driven control highlights his early engagement with problems that have since become central to the field. His research underscores the difficulty of building truly autonomous robots that can perceive, model, and navigate the world without human intervention, making his efforts a valuable stepping stone for students and engineers tackling the complexities of real-world robotics.
Research Focus
Key Achievements
Top Papers
- 1