[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

[Robot Flocking: Sensors and Control]

Multi-agent systems AI Date: Jan 2010

A group of robots This paper discusses various kinds of robot sensory input, approaches to motor control and ways they could be used for flocking. Focus is put on vision and Gibsonian optic flow that could be utilised by robots with advanced behaviour.

Also, infrared sensors and their advantages and disadvantages are discussed. Finally, the paper gives an overview of currently available robots that demonstrate collective behaviour and speculates how and whether adding 2D-image-based vision could give an advantage in terms of higher-level behaviour.

DOWNLOAD PAPER


{Please enable JavaScript in order to post comments}

Adaptive Robot Controller

 A robot neural controller where obstacle-avoidance and random-walk neurons observe level of their irritation and randomly reconfigure their connections to motors when the irritation reaches a specified threshold is presented and tested.

Does Communication Make a Difference?

 This paper compares different animal groups from eusocial insect colonies to human society and discusses their mechanics and behaviour as agent systems. The main focus is on interaction between the agents and on how properties of a system like effectiveness or predictability are affected by these interactions.

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.