Paresh Sao
Papers
1
Total Citations
5
H-Index
1
About
Paresh Sao is a researcher whose work sits at the intersection of robotics and cloud computing, with a particular focus on solving the Simultaneous Localization and Mapping (SLAM) problem. His key research areas include cloud robotics, autonomous navigation, and distributed robotic systems. Sao’s major contribution is a comprehensive review of cloud-based frameworks for SLAM, which systematically analyzed how offloading computationally intensive tasks to the cloud can enhance robotic perception and mapping capabilities. This work, published in 2017, has garnered 5 citations and serves as a foundational reference for researchers exploring the integration of cloud infrastructure with robotic systems. By addressing the scalability and computational limitations of onboard processing, Sao’s review highlighted practical pathways for deploying more intelligent and resource-efficient robots. His research is particularly relevant for applications in autonomous vehicles, service robotics, and industrial automation. Through his synthesis of existing frameworks and identification of key challenges, Paresh Sao has helped shape the direction of cloud robotics research, making his work a valuable starting point for students and researchers entering this dynamic field.
Research Focus
Key Achievements
Top Papers
- 1