Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.800569
Title: The Collinear Mecanum Drive
Author: Watson, Matthew T.
Awarding Body: University of Sheffield
Current Institution: University of Sheffield
Date of Award: 2019
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Abstract:
This thesis focuses on the modelling, analysis, and control of a novel robot locomotion system known as the Collinear Mecanum Drive (CMD). The CMD utilises three or more collinear Mecanum wheels to generate omnidirectional motion, whilst simultaneously dynamically balancing. By dynamically balancing, the ground footprint of a robot utilising a CMD can be designed to be arbitrarily thin, only lower bounded by choice of wheel diameter. The omnidirectional manoeuvrability of the CMD in combination with this narrow footprint allows for the navigation of much smaller gaps between obstacles than existing omnidirectional locomotion methods, achieved by translating directly along the common wheel rotation axis. This provides improved manoeuvrability in confined or cluttered environments. Being a dynamically balanced system, the height of the center of mass of a robot driven by a CMD can be increased without requiring a proportional increase in the width of the ground footprint so as to avoid toppling during acceleration or disturbance, as would be the case for existing statically stable omnidirectional locomotion methods. The CMD therefore promises to enable the creation of tall, space-efficient robots of more human-like form factors, that are better able to navigate the confined and cluttered environments commonly encountered in the home, office, and retail personal robotics sectors, and in the manufacturing and warehousing mobile industrial robotics sectors. This thesis derives and analyses the CMD's kinematics and dynamics models, explores a variety of control approaches, and develops the trajectory planning methods necessary for the autonomous navigation of an environment. It is hoped that this locomotion technology will see application across a range of existing and future mobile robotics sectors.
Supervisor: Gladwin, Daniel T. ; Prescott, Tony J. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.800569  DOI: Not available
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