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03/08/2021 2:44am
Amazon’s New Patent Wants to Combine #drones with Trucks for Deliveries [LINK]
27/07/2021 3:35am
What is the best #simulation tool for #robotics ? A useful article for those considering different options at the m… [LINK]
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RT @hardmaru: Nice article from Unity about multi-agent RL DodgeBall Some strategies that emerged include an agent dedicated to defend the…
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RT @joefresna: Check out the latest *special* issue of Swarm Intelligence @SpringerNature on "Collective decision making in living and arti…
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High quality code is actually CHEAPER to produce in the long run - a great article that I absolutely stand behind!… [LINK]

[Motosu: The Content Management System]

Web Bash script Date: Feb 2017

Motosu Project website: http://motosu.co.uk
Technologies used: PHP, MySQL, JavaScript, Model-View-Controller, CodeIgniter, CSS, RESTful Web Services, Bash scripts, Git

Motosu is a Content Management and a Web Hosting System that takes on Word Press by giving users easy-to-understand interface and content creation.

My roles in the project involved design and development of the front-end and back-end systems including the database and managing iterative development. I worked with a junior developer and a server administrator.

The code consists of the main content management application that gets duplicated for each new website and a set of bash scripts and super-admin interfaces for automatic website creation and maintenance. A customer can either register their own domain and redirect to a Motosu-managed web site or request a new Motosu subdomain to be created for them. The website editor allows the user to create new content using a WYSIWYG editor, manage web site administrators, define responsive layouts and styles for the whole website and for individual pages, use a number of "modules" such as a gallery browser, a Twitter feed, etc. and easily setup complex parallax effects, all without having to type a single line of code.



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pyCreeper

The main purpose of pyCreeper is to wrap tens of lines of python code, required to produce graphs that look good for a publication, into functions. It takes away your need to understand various quirks of matplotlib and gives you back ready-to-use and well-documented code.

Novelty detection with robots using the Grow-When-Required Neural Network

The Grow-When-Required Neural Network implementation in simulated robot experiments using the ARGoS robot simulator.

Fast Data Analysis Using C++ and Python

C++ code that processes data and makes it available to Python, significantly improving the execution speed.

Designing Robot Swarms

This project looks at the challenges involved in modeling, understanding and designing of multi-robot systems.

Robustness in Foraging E-puck Swarms Through Recruitment

Swarms of five e-puck robots are used in a semi-virtual environment, facilitated by the VICON positioning system. Recruitment can make swarms more robust to noise in robot global positioning data.