Bharath Kumar Adinarayan

Landing-a-SpaceX-Falcon-heavy-using-Proximal-Policy-Optimization-. Landing a SpaceX Falcon Heavy Rocket in simulation using Reinforcement learning. Reinforcement learning is a technique that lets an agent learn how best to act in an environment using rewards as its signal. OpenAI released a library called Gym that lets us train AI agents really easily. We'll also use Stable Baselines and gym libraries to build an RL agent capable of landing a rocket perfectly. The specific algorithm we will be using is called proximal policy optimization, this is an improved version of actor-critic algorithm.

CaLiB. Automatic Lidar-Camera Extrinsic Calibration based on Natural Features in the environment.

robotlearning-2024. Coursework 2024

Box2Seg. Box2Seg is a semantic annotation tool but faster.

Quantum-Computing-in-Python. Generating Random numbers in a quantum computer

NALU. Neural Arithmetic Logic Units (NALU) is an architecture that represents numerical quantities as linear activations which are manipulated using primitive arithmetic operators, controlled by learned gates.

Unitree-hrl. Unitree Go1 Repository for HRL (Bonn)

awesome-robot-learning. A curated list of robot learning links, papers, videos, ppt and slides.

Image_classifier_using_Keras. Image Classification using Convolutional Neural Nets and Keras. This classifier uses LeNet-5, a pioneering 7-level convolutional network by LeCun et al in 1998 that classifies digits.

Auto-Documentor. This project automatically documents the functions in a python code.

ycnvifnb. Yolo-based object detector for beverage containers detection.