Srivatsav Kamarajugadda
Papers
1
Total Citations
15
H-Index
1
About
Srivatsav Kamarajugadda is a researcher focused on autonomous vehicle control systems, with a particular emphasis on obstacle avoidance and model predictive control (MPC). His most-cited work, "Obstacle Avoidance Using Model Predictive Control: An Implementation and Validation Study Using Scaled Vehicles" (2020), has garnered 15 citations, demonstrating its relevance in the field of intelligent transportation. In this study, Kamarajugadda bridges theoretical control algorithms with practical validation, using scaled vehicles to test MPC-based obstacle avoidance strategies—a critical step toward safer autonomous navigation. His contributions lie in advancing real-time decision-making for self-driving cars, addressing challenges like path planning and dynamic obstacle response. By combining simulation and experimental validation, his work offers a replicable framework for researchers and engineers developing autonomous systems. Kamarajugadda’s research aligns with broader efforts in adaptive cruise control, lane keeping, and lane following, contributing to the growing body of knowledge that aims to make autonomous vehicles more reliable and efficient. His work is particularly valuable for students and practitioners seeking hands-on, validated approaches to autonomous control.
Research Focus
Key Achievements
Top Papers
- 1