Computer Vision and Robotic Perception
Detection, segmentation, depth estimation, geometric vision, visual odometry, and perception pipelines for robots operating outside controlled laboratory settings.
Computer Vision · Robotics · SLAM · Sensor Fusion
Building visual intelligence for real-world robotic systems.
I work on computer vision, robotic perception, SLAM, 3D reconstruction, GNSS/IMU/camera sensor fusion, and embedded AI for field environments such as orchards, farms, mines, roads, and industrial sites.
About
Vision and Robotics for Intelligent Sensing.
My research goal is to develop deployable perception systems that combine algorithms, sensors, hardware, and field data.
Research identity
I focus on the intersection of computer vision, robotics, 3D perception, sensor fusion, and embedded systems. My current work connects orchard-scale reconstruction and yield estimation with broader field robotics problems in agriculture, mining, infrastructure inspection, and autonomous sensing.
Computer Vision
Robotic Perception
SLAM
Sensor Fusion
Embedded AI
Research
Research themes
A focused research program around deployable visual intelligence for unstructured outdoor environments.
SLAM and 3D Reconstruction
Metric-scale mapping, camera trajectory estimation, factor-graph optimization, stereo vision, semantic landmarks, and large-scale 3D reconstruction.
GNSS/IMU/Camera Sensor Fusion
Georeferenced localization and mapping using GNSS, visual information, inertial data, filtering, optimization, and field trajectory evaluation.
Embedded AI and Field Deployment
Hardware-aware perception on edge devices, including Jetson-class platforms, sensor interfaces, real-time constraints, latency, and robustness.
Projects
Current and emerging directions
Orchard-scale 3D reconstruction
Georeferenced reconstruction of orchard environments using cameras, GNSS, SLAM, semantic landmarks, and AI-based perception for yield-estimation workflows.
Field robotics for agriculture and mining
Translating visual perception and robotic mapping methods across orchards, farms, mine roads, tunnels, infrastructure sites, and industrial inspection environments.
Edge perception systems
Deployable sensing systems using stereo cameras, embedded AI, GNSS, IMU, and real-time software for outdoor robotic applications.
Publications
Publication record
For the most current and verified publication list, please use my ORCID and Google Scholar profiles.
Teaching and students
Open to motivated students
I am interested in working with B.Tech, M.Tech, and PhD students who want to build systems in computer vision, robotics, SLAM, sensor fusion, embedded AI, and real-world field deployment.
Good starting topics include stereo visual SLAM, GNSS-aided mapping, 3D reconstruction baselines, semantic landmark detection, Jetson deployment, and field robotics for agriculture and mining.
Teaching interests
- Digital Image Processing
- Computer Vision and Robotic Perception
- Digital Signal Processing
- Machine Learning and Artificial Intelligence
- Sensor Fusion for Autonomous Systems
- Embedded AI and Edge Computing
Contact
Academic and professional links
For collaboration, student projects, and research discussions, please email me with a specific subject and a short technical context.