Developer Portfolio

Novel Variable Friction Gripper (Yet to be Published in IROS 2025)

Developed a robotic finger system that uses targeted surface vibrations to dynamically control friction, enabling precise in-hand object sliding and rotation.

Real Time Road Traffic Visualization

I Built a Tesla-inspired perception pipeline with YOLO, ONNX, and Mask R-CNN for real-time 3D scene understanding including object detection and localization with an accuracy of 92%.

Vision-Based Robotic Manipulation

Designed a robotic grasping system for conveyor environments using YOLO for object detection and GGCNN for grasp prediction, achieving 92% accuracy. Implemented closed-loop pose correction to enhance grasp stability under conveyor vibrations.

VIO Using MSCKF

I built a stereo vision-aided odometry system using a Multi-State Constraint Kalman Filter (MSCKF) that fuses IMU and camera data for precise real-time trajectory estimation, achieving a ~0.07 m median error on the EuRoC dataset.

Deep VIO

I created a deep learning-based VIO framework combining CNNs, LSTM, and FlowNet to fuse visual and inertial data, reaching ~79% accuracy for relative pose prediction on the validation set.

Edge Detection

I developed a Probability of Boundary method that outperforms classic edge detectors by leveraging texture, brightness, and color cues, and also compared four CNN architectures on CIFAR-10 under data augmentation and hyperparameter tuning.

Image Stitching

I developed a panoramic image stitching pipeline, combining classical methods (corner detection, homography via RANSAC) and deep-learning-based (supervised and unsupervised) approaches to seamlessly warp and blend multiple images into a single panorama.

Sfm & NeRF

I implemented a Structure-from-Motion workflow—estimating camera poses, 3D points, and bundle adjustment—and integrated a Neural Radiance Field (NeRF) for volumetric rendering, enabling novel view synthesis from sparse image inputs.

Camera Calibration

Using Zhang's Camera Calibration, I estimated intrinsic and extrinsic parameters (including radial distortion), then minimized reprojection errors to achieve precise camera calibration and consistent image rectification.

Anuj Jagetia

Roboticist Specialized in Machine Learning

Experience

Novel Variable Friction Gripper (Yet to be Published in IROS 2025)

Real Time Road Traffic Visualization

Vision-Based Robotic Manipulation

VIO Using MSCKF

Deep VIO

Edge Detection

Image Stitching

Sfm & NeRF

Camera Calibration

Education

Master's of Science

Bachelor's of Technology

My Skills

Technical Skills

Get in Touch!