Devraj Priyadarshi's Projects
My BTP github repository.
A jekyll template derived from Minimal Mistakes and inspired by academicpages. To see an example of what a webpage might look like with this repo, see matthewkirby.github.io.
Course Assignment for Artificial Intelligence: Foundation and Application
An attempt at autonomous landing through coupled perception-action optimization.
Pytorch package to compute Chamfer distance between point sets (pointclouds).
Neural Transfer Style is one of the most amazing applications of Artificial Intelligence in a creative context. In this project, we choose an art painting style and transfer its style to a chosen image, creating stunning results.
Config files for my GitHub profile.
Website
If you dont see my codes, its because they're in my notebooj
An Open Flexible Quadrotor Simulator
Gazebo models and worlds gathered from various sources
Universal grid map library for mobile robotic mapping
PyBullet Gym environments for single and multi-agent reinforcement learning of quadcopter control
A universal flight control tuning framework
A light & simple & responsive page for academic websites on Hexo, crafted from academicpages on Jekyll.
A project to implement the work of "High-Quality Single-Shot Capture of Facial Geometry" for creating High Quality Face Mesh
Open source robotics simulator. Through Ignition Gazebo users have access to high fidelity physics, rendering, and sensor models. Additionally, users and developers have multiple points of entry to simulation including a graphical user interface, plugins, and asynchronous message passing and services. Ignition Gazebo is derived from Gazebo, and represents over 16 years of development and experience in robotics and simulation. This library is part of the Ignition Robotics project.
Public Code Repository of the iRotate Active SLAM for Omnidirectional robots at the Max Planck Institute for Intelligent Systems, Tรผbingen
ROS packages for multi robot exploration
An open visual-inertial mapping framework.
A repo containing papers in the field of control (and perception).
Self-supervised method for completing partial LiDAR point clouds. Trained and tested on ShapeNet and SemanticKITTI in TensorFlow. (BMVC 2021)
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
pytorch implementation for "PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation" https://arxiv.org/abs/1612.00593
Implementation of the Chamfer Distance as a module for pyTorch