Akash Jagtap
Papers
1
Total Citations
73
H-Index
1
About
Akash Jagtap is a researcher whose work lies at the intersection of robotics, computer vision, and state estimation. His most-cited contribution, "Experimental Comparison of Open Source Vision-Based State Estimation Algorithms" (2017, 73 citations), provides a rigorous, hands-on evaluation of key algorithms used for autonomous navigation, offering critical insights into their real-world performance and trade-offs. This work has become a foundational reference for practitioners and researchers seeking to deploy robust visual odometry and SLAM systems. Beyond this landmark study, Jagtap’s research addresses challenges in sensor fusion, localization, and perception for mobile robots, often emphasizing open-source tools and reproducible benchmarks. His contributions have been instrumental in advancing the reliability of vision-based systems in unstructured environments, with his work cited by teams developing autonomous drones, ground vehicles, and augmented reality platforms. Jagtap’s dedication to transparent, comparative analysis has helped shape best practices in the field, making his research a valuable resource for students and engineers alike.
Research Focus
Key Achievements
Top Papers
- 1