BTech project
The project integrates real-time tracking mechanisms to ensure consistent and reliable lane detection over consecutive frames. By employing techniques such as Kalman filtering and weighted moving average, the system predicts and tracks the lane lines, providing smooth and continuous lane information.
BTech project
This project is about detecting obstacles from highly sparse LiDAR point cloud and tracking multiple objects in real time.
BTech project
Implemented facial keypoints detection using deep learning techniques, achieving accurate localization of key facial landmarks such as eye corners, nose tip, and mouth corners
BTech project
Led development of 'CarOS,' A Raspberry Pi-based vehicle automation system, integrating computer vision and IoT technologies. Designed real-time object detection and lane tracking using OpenCV, enabling autonomous navigation. Implemented a user-friendly web interface for remote control and monitoring, enhancing user experience. Leveraged Python,cpp and ADAS framework to ensure seamless communication between onboard sensors and the central control hub. Demonstrated strong skills in embedded systems, computer vision, and IoT to create a robust and adaptable automotive solution
World L&T Techgium Compitition
Imported Designed crane model with Lidar,camera and IMU sensor in it , converted into URDF format to export it to ROS for automation. The real time tracking of objects done by obtaining frustrum and applying Pose Graph based SLAM approach for mapping of landmarks and used Kmeans algorithm for data clustering ,fusion done on Ros with pcl library ,made a prototype of this problem statement
Final Year Project
A farming robot with automatic navigation, weed detection system, designed for navigating between crops, across farms and providing aid in multiple operations required by farmers, specific in automatic weed spraying system.
11/2021 - 03-2022
05-2021 - 11-2021
05/2022 - 07/2022