[Tweets]

20/04/2018 6:16pm
DART: Noise injection for robust imitation learning via @Robohub [LINK]
18/04/2018 12:44am
RT @UomRobotics: Check out Festo's New Bionic Robots Include Rolling Spider, Flying Fox [LINK] @Festo are real world leade…
17/04/2018 8:47pm
A new exciting #postdoc position in #swarm #robotics at @unisouthampton [LINK]
12/04/2018 12:24am
RT @wjscheirer: Pre-print of the long awaited position paper: "The Limits and Potentials of Deep Learning for Robotics." Provocative stuff…

[Does Communication Make a Difference?]

Project: Designing Robot Swarms
Date: Apr 2010
Tags: swarm

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.

DOWNLOAD PAPER


{Please enable JavaScript in order to post comments}

[You might also be intested in...]

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.
Robot Flocking: Sensors and Control
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.
V-REP, Gazebo or ARGoS? A robot simulators comparison
Let’s have a look at three commonly used open-source simulators for robotics: V-REP, Gazebo and ARGoS, to find out which one suits your project the best.
Designing Effective Roadmaps for Robotics Innovation
Automated factories, autonomous delivery drones, self-driving cars: these and similar technologies will soon touch every aspect of our lives. An engaging discussion about how these technologies are regulated and innovated took place at the IROS 2017 conference.
The Information-Cost-Reward framework for understanding robot swarm foraging
The Information-Cost-Reward (ICR) framework relates the way in which robots obtain and share information about where work needs to be done to the swarm’s ability to exploit that information in order to perform work efficiently in the context of a particular task and environment.
Behaviour-Data Relations Modelling Language For Multi-Robot Control Algorithms
Behaviour-Data Relations Modeling Language (BDRML) explicitely represents behaviours and data that robots utilise, as well as relationships between them. This allows BDRML to express control algorithms where robots cooperate and share information with each other while interacting with the environment.