Mehak Jindal
Papers
1
Total Citations
17
H-Index
1
About
Mehak Jindal’s research lies at the intersection of autonomous maritime systems, 3D point cloud processing, and computer vision, with a focus on enabling safe, unmanned vessel operations. Her most cited work, “Bollard Segmentation and Position Estimation From Lidar Point Cloud for Autonomous Mooring” (2021, 17 citations), introduces a novel method for detecting and localizing bollards—critical on-shore structures—from lidar data. This contribution directly addresses a key challenge in autonomous mooring, where a ship must precisely tie to a rigid dock fixture without human intervention. By leveraging shape features and segmentation algorithms, Jindal’s approach enhances the reliability of object detection in complex maritime environments, laying groundwork for fully autonomous navigation. Her work has been recognized for its practical impact on the emerging field of smart shipping, where reducing human error and improving efficiency are paramount. With growing interest in autonomous vessels, Jindal’s contributions continue to influence both academic research and industrial applications in maritime robotics.
Research Focus
Key Achievements
Top Papers
- 1