Sanat Mharolkar
Papers
3
Total Citations
46
H-Index
2
About
Sanat Mharolkar is a rising researcher at the forefront of robust perception for autonomous systems, specializing in multi-modal sensor fusion and simultaneous localization and mapping (SLAM). His work addresses a critical vulnerability in autonomous navigation: the failure of conventional LiDAR- and visual-based SLAM in adverse conditions such as rain, snow, smoke, and fog. Mharolkar’s key contributions center on leveraging 4D radar, thermal cameras, and IMU sensors to create resilient perception systems. His most cited work, "NTU4DRadLM" (33 citations), introduces a pioneering 4D radar-centric multi-modal dataset specifically designed for robust localization and mapping in challenging environments. He further advanced the field with "RGBDTCalibNet" (11 citations), an end-to-end online calibration framework that seamlessly aligns 3D LiDAR, RGB, and thermal cameras—eliminating the tedious offline calibration process and enabling reliable day-and-night perception. Additionally, his work on high-fidelity teleoperation for heavy-duty vehicles demonstrates a practical application of his research, providing a crucial backup for autonomous systems in off-road scenarios. Through these innovations, Mharolkar is helping to push the boundaries of all-weather, round-the-clock autonomous navigation.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3High-fidelity Teleoperation for Heavy-duty Vehicles2 citations · 2023