[Tweets]

10/12/2018 7:08pm
RT @karpathy: Incredible NeurIPS talk from @drmichaellevin on "Bioelectric Computation Outside the Nervous System" [LINK]
06/12/2018 6:39pm
We are looking for 2x part-time Java developers to work on an awesome editor for a multi-agent systems modelling la… [LINK]
06/12/2018 5:12pm
Excited to announce that we have been awarded the @EPSRC Impact Accelerator Kickstarter Award in collaboration with… [LINK]
03/12/2018 8:39pm
RT @BristolRobotLab: Cafe opens in Tokyo staffed by robots controlled by paralyzed people [LINK] via @RocketNews24En

[Welcome to my website]

Lenka Pitonakova I am a Research Associate in Applied Mathematics and Computer Science at the University of Bristol. My research area is unsupervised learning with self-organised neural networks. Previously, I was a Post-Doctoral Research Fellow at the University of Southampton and worked at the Bristol Robotics Laboratory in the area of swarm robotics. My wider research interests include the emergence of intelligence in embodied systems and human-robot interaction. I post about research on Twitter, LinkedIn and in my blog.

Apart from doing research, I am also a software developer with extensive experience in different languages, platforms and toolkits. My passion is computer games developent and I am always working on a personal side project when the time allows. Apart from programming, I enjoy creative writing, making music, drawing and studying Zen philosophy.

I have a PhD in Simulation of Complex Systems, a Masters in Evolutionary and Adaptive Systems and a BSc in Games Development. [Contact and more info]

Selected projects

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

Simulation models C++ Bash script The Grow-When-Required Neural Network implementation in simulated robot experiments using the ARGoS...

Designing Robot Swarms

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

Robustness in Foraging E-puck Swarms Through Recruitment

Robots Multi-agent systems Swarms of five e-puck robots are used in a semi-virtual environment, facilitated by the VICON...

V-REP, Gazebo or ARGoS? A robot simulators comparison

Robots Multi-agent systems C++ AI Tutorials Let’s have a look at three commonly used open-source simulators for robotics: V-REP, Gazebo and...

The Hive Mind

Games Flash AI The Hive Mind is a sci-fi puzzle game about insect-inspired construction with robots. The player...

Linee the line follower

Robots Linee is a line following robot that instead of being programmed, uses a fully analogue controller...
 

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.