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activelifelonglearning

ai_for_robotics

Programming Exercises Accompanying the Lecture "Artificial Intelligence for Robotics"

airsim

Open source simulator for autonomous vehicles built on Unreal Engine / Unity, from Microsoft AI & Research

anml

A Nonlinear Modeling Library (ANML) :pig: :tiger: :bear:

arc-robot-vision

MIT-Princeton Vision Toolbox for Robotic Pick-and-Place at the Amazon Robotics Challenge 2017 - Robotic Grasping and One-shot Recognition of Novel Objects with Deep Learning.

artificial-intelligence-for-robotics

Solution to the programming assignments in Artificial Intelligence For Robotics by Udacity

audio-denoising-using-digital-filters

A simple application based project in the field of Digital Signal Processing. An attempt was made to clean up a deterministic noise corrupted voice audio clipping using a combination of digital filtering techniques. The processing and simulation were carried out on MATLAB.

autonomous-landmine-detection-quad-copter

MESA spring 2016 project

awesome-robotics

A list of awesome Robotics resources

awesome-robotics-libraries

:sunglasses: A curated list of robotics libraries and software

boosting_da

Boosting for Domain Adaptation

bregman-correntropy-conditional-divergence

Bregman-Correntropy divergence on Conditional Distributions

consensus-problem-in-directed-networks-with-nonlinear-multi-agents

datasets

publicly available data sets for machine learning

deeplearningrobotics

for integrating Deep Learning and Robotics

deeplstm

Deep LSTM for highly nonlinear system modeling

domain-adaptation-toolbox

This project contains the papers, algorithms, notes that I read, implement, write in domain adaptation.

dtmf-controlled-landmine-detection-rover

effective_robotics_programming_with_ros

Effective Robotics Programming with ROS

ella

An implementation of ELLA

ella-1

fenek

Live Coding in JavaScript and VR

gitbook_sensorfusion

grid_map

Universal grid map library for mobile robotic mapping

hratc2017_expertinos_team

The Anti-Personnel Mine Ban Convention is one of the world's most widely accepted treaties with 162 States Parties agreeing not to use, stockpile, produce or transfer antipersonnel mines. Although this has had profound impact worldwide, there is a non-negligible conflict legacy that still has provoked terrible consequences. According to the UN Mine Action Service, landmines kill 15,000-20,000 people every year (mostly children) and maim countless more across 78 countries. Demining efforts cost US$ 300-1000 per mine, and, for every 5000 mines cleared, one person is killed and two are injured. Thus, clearing post-combat regions of landmines has proven to be a difficult, risky, dangerous and expensive task with enormous social implications for civilians. Motivated by these considerations, the IEEE Robotics & Automation Society’s Special Interest Group on Humanitarian Technology (RAS–SIGHT) is inviting the academic and non-academic community to participate in the fourth Humanitarian Robotics and Automation Technology Challenge (HRATC) at the 2017 International Conference on Robotics and Automation (ICRA’17). This fourth HRATC edition will follow the footsteps of previous ones and continue to focus on promoting the development of new strategies for autonomous landmine detection using a mobile (ground) robot. HRATC Challenge has three phases: 1) Simulation Phase, 2) Testing Phase, and 3) Finals Phase. The strategies developed by the participating teams will be according to the following criteria: exploration time and environmental coverage; detection and classification quality; and landmine avoidance. Teams will be progressively eliminated after each phase and the remaining teams would move on to the next phase culminating in the Challenge (Finals) phase at ICRA’17.

humble-peer-amtl

hybrid-sindy

Sparse Identification of Nonlinear Dynamics for Hybrid Systems

hypersim

Nonlinear simulation of hypersonic flight dynamics, made with MATLAB and FlightGear

image-processing-toolkit

some useful Matlab programs for image processing

imageclassification

Deep Learning: Image classification, feature visualization and transfer learning with Keras