Dynamic networks for robotic control and behaviour selection in interactive environments

Peach, Brian

Computer science
February 2019

Thesis or dissertation


Rights
© 2019 Brian Peach. All rights reserved. No part of this publication may be reproduced without the written permission of the copyright holder.
Abstract

Traditional robotics have the capabilities of the robot hard coded and have the robot function in structured environments (structured environments are those that are predefined for a given task). This approach can limit the functionality of a robot and how they can interact in an environment. Behaviour networks are reactive systems that are able to function in unstructured dynamic environments by selecting behaviours to execute based on the current state of the environment. Behaviour networks are made up of nodes that represent behaviours and these store an activation value to represent the motivation for that behaviour. The nodes receive inputs from a variety of sources and pass proportions of that input to other nodes in the network.

Behaviour networks traditionally also have their capabilities predefined. The main aim of this thesis is to expand upon the concepts of traditional robotics by demonstrating the use of distributed behaviours in an environment. This thesis aims to show that distributing object specific data, such as; behaviours and goals, will assist in the task planning for a mobile robot.

This thesis explores and tests the traditional behaviour network with a variety of experiments. Each experiment showcases particular features of the behaviour network including flaws that have been identified. Proposed solutions to the found flaws are then presented and explored. The behaviour network is then tested in a simulated environment with distributed behaviours and the dynamic behaviour network is defined. The thesis demonstrates that distributed behaviours can expand the capabilities of a mobile robot using a dynamic behaviour network.

Publisher
Department of Computer Science, The University of Hull
Supervisor
Robinson, Peter A.; Davis, Darryl N., 1955-; Cheng, Yongqiang
Qualification level
Doctoral
Qualification name
PhD
Language
English
Extent
4 MB
Identifier
hull:17290
QR Code