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leo-satellite-dynamics

Here I am programming the translational dynamics of a low earth satellite using ode45 in Matlab. I have adapted the angle of inclination to the 51.6-degree position of the ISS. All my code is open for development.

leo_stm

Code written for a summer project "Space Traffic Control: Monitoring Low Earth Orbit" carried out at the Institute for Astronomy, University of Edinburgh, in 2019.

masac

Jax and Torch Multi-Agent SAC on PettingZoo API

mpc-cbf

"Safety-Critical Model Predictive Control with Discrete-Time Control Barrier Function" by J. Zeng, B. Zhang and K. Sreenath https://arxiv.org/abs/2007.11718

mpconstellation

Model Predictive Control for Satellite Constellations

multi-agent-evolutionary-rl

Implementation of Evolutionary Strategies with Multi-Agent Deep Reinforcement Learning in PettingZoo Environments

near-earth-objects-classifier

Machine Learning model to detect potentially hazardous NEOs (Near Earth Objects) from its orbital data

object-background-region-separation-in-depth-image-using-k-means-clustering-algorithm

Preliminary Study for Depth Segmentation, this paper will be proceeding in KISM2021-Fall

object-detection-and-tracking

object-detection-tracking

optimization-for-leo-satellites-network

The current generation of LEO constellations assumes that each LEO satellite covers a ground area regardless of the number of end users or terminals operating in the same area. The satellite solution to the communication problem, both in terms of reach and quality, is lacking when we talk about optimization in QoS aspects.

orbit-maneuver-rl

A set of tools and experiments related to the optimization of impulsive maneuvers for orbital transfers of spacecraft

otter-usv-target-tracking-controllers

Master thesis repo for implementation of Model Predictive Controller and reinforcement learning (RL) controller

phd-code

pld-uav

Two Datasets for Power Line Detection in UAV Images

plgan-for-power-line-segmentation

Generative Adversarial Networks for Power-Line Segmentation in Aerial Images

predicting-orbits

Trained RNNs (LSTM) that are used in predicting how Orbital Elements will evolve in time, using only a fraction of the computational power of numerical methods.

r-fcn

R-FCN: Object Detection via Region-based Fully Convolutional Networks

radar-camera-fusion-depth

Depth Estimation from Camera Image and mmWave Radar Point Cloud

radargnn

A graph neural network for the segmentation and object detection in radar point clouds.

rc-pda

recurrent-ppo

A Reinforcement Learning Project using PPO + LSTM

rlforutracking

Deep Reinforcement Learning (RL) algorithms for underwater target tracking with Autonomous Underwater Vehicles (AUV)

rl_path_tracking

robot_target_tracking

Research Project on Multi-robot Target Tracking via Deep Reinforcement Learning

sac-rcbf

safe_exp_env

Thrid-party safety-gym safe exploration environments for autonomous driving. Also environment used for IROS 2021 paper: Model-based Constrained Reinforcement Learning using Generalized Control Barrier Function

safe_reinforcement_learning

Repository containing the code for the paper "Safe Model-Based Reinforcement Learning using Robust Control Barrier Functions". Specifically, an implementation of SAC + Robust Control Barrier Functions (RCBFs) for safe reinforcement learning in two custom environments

satellite-orbit-prediction

Predicting the position of satellites is one of the big challenges in astronomy.

search-and-rescue-sar-at-sea-with-uav

A Novelty Approach to Emulate Field Data Captured by Unmanned Aerial Vehicles for Training Deep Learning Algorithms Used for Search-and-Rescue Activities at Sea