Show simple item record

dc.contributor.supervisorCangelosi, Angelo
dc.contributor.authorRuini, Fabio
dc.contributor.otherFaculty of Science and Technologyen_US
dc.date.accessioned2013-06-21T08:41:27Z
dc.date.available2013-06-21T08:41:27Z
dc.date.issued2013
dc.identifier10143836en_US
dc.identifier.urihttp://hdl.handle.net/10026.1/1549
dc.descriptionFull version unavailable due to 3rd party copyright restrictions.
dc.description.abstract

The work presented herein focuses on the design of distributed autonomous controllers for collective behaviour of Micro-unmanned Aerial Vehicles (MAVs). Two alternative approaches to this topic are introduced: one based upon the Evolutionary Robotics (ER) paradigm, the other one upon flocking principles. Three computer simulators have been developed in order to carry out the required experiments, all of them having their focus on the modelling of fixed-wing aircraft flight dynamics. The employment of fixed-wing aircraft rather than the omni-directional robots typically employed in collective robotics significantly increases the complexity of the challenges that an autonomous controller has to face. This is mostly due to the strict motion constraints associated with fixed-wing platforms, that require a high degree of accuracy by the controller. Concerning the ER approach, the experimental setups elaborated have resulted in controllers that have been evolved in simulation with the following capabilities: (1) navigation across unknown environments, (2) obstacle avoidance, (3) tracking of a moving target, and (4) execution of cooperative and coordinated behaviours based on implicit communication strategies. The design methodology based upon flocking principles has involved tests on computer simulations and subsequent experimentation on real-world robotic platforms. A customised implementation of Reynolds’ flocking algorithm has been developed and successfully validated through flight tests performed with the swinglet MAV. It has been notably demonstrated how the Evolutionary Robotics approach could be successfully extended to the domain of fixed-wing aerial robotics, which has never received a great deal of attention in the past. The investigations performed have also shown that complex and real physics-based computer simulators are not a compulsory requirement when approaching the domain of aerial robotics, as long as proper autopilot systems (taking care of the ”reality gap” issue) are used on the real robots.

en_US
dc.description.sponsorshipEOARD (European Office of Aerospace Research & Development), euCognitionen_US
dc.language.isoenen_US
dc.publisherUniversity of Plymouthen_US
dc.subjectMAVsen_US
dc.subjectCollective behaviouren_US
dc.subjectAutonomous Roboticsen_US
dc.subjectEvolutionary computationen_US
dc.subjectNeural networksen_US
dc.subjectGenetic Algorithmsen_US
dc.subjectEvolutionary Roboticsen_US
dc.subjectFlocking behaviouren_US
dc.subjectSimulationen_US
dc.subjectMulti-Agent Systemen_US
dc.titleDistributed Control for Collective Behaviour in Micro-unmanned Aerial Vehiclesen_US
dc.typeDoctorateen_US
plymouth.versionEdited versionen_US


Files in this item

Thumbnail
Thumbnail
Thumbnail

This item appears in the following Collection(s)

Show simple item record


All items in PEARL are protected by copyright law.
Author manuscripts deposited to comply with open access mandates are made available in accordance with publisher policies. Please cite only the published version using the details provided on the item record or document. In the absence of an open licence (e.g. Creative Commons), permissions for further reuse of content should be sought from the publisher or author.
Theme by 
@mire NV