End to End Autopilot Perception Playbook

Example city simulation for autonomous vehicles in Gazebo Classic.

In this project, I used Python and TensorFlow to classify traffic signs. Dataset used: German Traffic Sign Dataset. This dataset has more than 50,000 images of 43 classes. I was able to reach a +99% validation accuracy, and a 97.3% testing accuracy.

Deep neural networks and convolutional neural networks to classify German traffic signs.

Multi-Object Tracking and Trajectory Prediction. This repository contains all codes written for SUMMER RESEARCH INTERNSHIP (2021) at AI and Robotics Park (ARTPARK), IISc Bangalore

📐 Personal GitHub web page. Based on the minimal-mistakes Jekyll theme.

Learning resources for autonomous robot and self-driving vehicle systems

2D/ 3D object detection, segmentation, depth estimation for self-driving car

Engineering Integrated Design Project

This is a computer vision project for solving the problem of lane detection in autonomous driving vehicles. The project uses simple thresholding based techniques in L*a*b color space. Programming has been done in C++ using OpenCV library.

Udacity SDC Traffic sign recognition project 2

E-Scooter Rider Detection and Classification in Dense Urban Environments

A combination of reinforcement and evolutionary learning are used in an attempt to allow autonomous vehicles to learn behaviors necessary for the navigation of an intersection in a simple 2D traffic simulator. The open source AIM4 simulator developed by the Learning Agents Research Group at The University of Texas was extended to implement a spe…

My personal website

Motion Forecasting for Autonomous Vehicles using the Argoverse Motion Forecasting Dataset

An approach to classify traffic signs with neural networks in TensorFlow. Project 2 of Udacity's Self-Driving Car Engineer Nanodegree Program.

Autonomous subsystem for an autonomous vehicle

Computer vision project on vehicle detection and tracking on roads

This repository is used to make a website that talks about my experience at MIT's 2016 Beaverworks Summer Institute, an engineering camp for rising high school seniors.

An advanced algorithm for lane detection utilizing different color space, thresholding techniques and sliding window search.