[Tweets]

23/03/2017 6:58pm
RT @BristolRobotLab: @BristolRobotLab researchers to create biomimetic forebrain for 3D-printed robot hands [LINK] @Lever
22/03/2017 12:49pm
RT @RethinkRobotics: Robots won’t take your job—they’ll help make room for meaningful work instead [LINK] via @qz [LINK]
21/03/2017 7:18pm
RT @SwarmDynamics: We offer a fully funded #PhD position at @UniLuebeck (Germany) in #swarm #robotics & evolutionary robotics [LINK]
17/03/2017 3:02pm
Choreographing automated cars could save time, money and lives [LINK]
14/03/2017 2:44pm
MIT develops #robots controlled by human brains [LINK]

[Task Allocation in Foraging Robot Swarms]

Project: Design Patterns for Robot Swarms
Date: Apr 2016
Tags: swarm :: robotics :: C++ :: A-Life

Robots foraging Autonomous task allocation is a desirable feature of robot swarms that collect and deliver items. When there are many robots in the swarm, or when collected items accumulate quickly in a drop-off location, congestion can prevent the swarm from working effectively. In such scenarios, self-regulation of workforce can prevent unnecessary energy consumption.

In this paper, we analyse bee-inspired self-regulation algorithms for robot swarms that deliver items into a single drop-off location.

We explore two types of self-regulation:
  • Non-social, where robots go to rest when they experience congestion
  • Social, where robots broadcast information about congestion to their team mates to tell them that they should rest

DOWNLOAD PAPERDOWNLOAD CODE

Outcome:
Performance of the swarms in various environments We show that both types of self-regulation can lead to improved energy efficiency and increase the amount of resource collected. More importantly, the rate at which information about congestion spreads through a swarm affects the scalability of the explored robot control strategies.

A slow information flow, characteristic for non-social self-regulation, leads to behaviour suitable for a larger number of experimental scenarios. On the other hand, fast information flow, achieved by social self-regulation, causes more extreme difference in performance across scenarios. Using swarms with faster information flow thus requires us to be more certain about the environmental conditions we employ our swarms in.

Publication:
Pitonakova, L., Crowder R. & Bullock, S. (2016). Task allocation in foraging robot swarms: The Role of Information Sharing. In Gershenson, C. et al. (eds.), Proceedings of the Fifteenth International Conference on the Synthesis and Simulation of Living Systems (ALIFE XV), MIT Press, 306-313.

Talk slides


{Please enable JavaScript in order to post comments}

[Blog]

Coding for tomorrow: Why is good code important?

"Why should I care about how my code is written, as long as it works?" I will argue here that well-structured and well-written code not...

[read full]

How Coding in Python Might Be Bad For You

7 reasons why coding in Python is like writing a really bad essay and getting away with it

[read full]

Book Review: Waking, Dreaming, Being

What is the self? Is it the basic nature of the mind or is it something perceived by the mind? I'd really recommend the book to anyone...

[read full]

Are Robot Swarms Like Brains?

I have recently explored a way of measuring how information flows within a robot swarm. I think that there is something intriguing behind...

[read full]