M. Sravanthi
Papers
2
Total Citations
5
H-Index
2
About
M. Sravanthi is a researcher at the forefront of embedded systems and robotics, specializing in adaptive FPGA-based accelerators for real-time human-robot interaction. Her work addresses critical challenges in autonomous navigation and perception, particularly in constrained or adverse environments. Her most cited paper (2024, 3 citations) introduces adaptive FPGA accelerators that enable service robots to predict human posture in indoor spaces, overcoming significant hurdles in real-time interaction within confined areas. This contribution is pivotal for enhancing the safety and responsiveness of collaborative robots. Earlier, her 2019 study (2 citations) pioneered a minimal-sensing approach for autonomous vehicle navigation in foggy conditions, demonstrating how computational efficiency can be achieved through reference-less object detection on FPGA platforms. By focusing on throughput optimization in practical environments, Sravanthi’s work bridges the gap between theoretical algorithms and deployable hardware solutions. Her research is particularly notable for its emphasis on low-latency, resource-constrained systems, making her a key contributor to the advancement of intelligent autonomous systems in both indoor service robotics and outdoor vehicular applications.
Research Focus
Key Achievements
Top Papers
- 1
- 2