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23/10/2018 2:43pm
RT @alexalcocerp: We are hiring a Professor in Robotics and Control at @OsloMet, permanent position, deadline 07.11 Do you know any potenti…
23/10/2018 2:42pm
RT @brianwong_BS: Good morning from the @Flourish_Cars media showcase at @BristolRobotLab! Lots to update on today on user and security tri…
17/10/2018 12:47pm
RT @GTheraulaz: Introducing the new Cuboids: a concentrate of high-techology to study flocking behavior. I will present this swarm robotic…
12/10/2018 7:28pm
RT @andy_adamatzky: Fantastic position is open to work in groundbreaking H2020 Project @evo_nano The successful candidate will work in an…

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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.