Markus Rittenbruch

Prof. Markus Rittenbruch


Research Focus & Metrics

Academic Career Length

29Years (1998-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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25 August 2020 in International Journal of Technology and Design Education
Verified
Journal Article
Closed access
PDF file
DZDing Zhou
Ding Zhou
RGRafael Gomez
Rafael Gomez
NWNatalie Wright
Natalie Wright
MRMarkus Rittenbruch
Markus Rittenbruch
JDJames P. Davis
James P. Davis

1 January 2013
Verified
Book Chapter
Closed access
PDF file
DFDaniel Filonik
Daniel Filonik
RMRichard Medland
Richard Medland
MFMarcus Foth
Marcus Foth
MRMarkus Rittenbruch
Markus Rittenbruch

9 February 2024 in Robotics
Verified
Journal Article
Open access
PDF file
YLYuan Liu
Yuan Liu
GCGlenda Caldwell
Glenda Caldwell
MRMarkus Rittenbruch
Markus Rittenbruch
MTMüge Belek Fialho Teixeira
Müge Belek Fialho Teixeira
ABAlan Burden
Alan Burden
MGMatthias Guertler
Matthias Guertler
The advent of Industry 4.0 has heralded advancements in Human–robot Collaboration (HRC), necessitating a deeper understanding of the factors influencing human decision making within this domain. This scoping review examines the breadth of research conducted on HRC, with a particular focus on identifying factors that affect human decision making during collaborative tasks and finding potential solutions to improve human decision making. We conducted a comprehensive search across databases including Scopus, IEEE Xplore and ACM Digital Library, employing a snowballing technique to ensure the inclusion of all pertinent studies, and adopting the PRISMA Extension for Scoping Reviews (PRISMA-ScR) for the reviewing process. Some of the important aspects were identified: (i) studies’ design and setting; (ii) types of human–robot interaction, types of cobots and types of tasks; (iii) factors related to human decision making; and (iv) types of user interfaces for human–robot interaction. Results indicate that cognitive workload and user interface are key in influencing decision making in HRC. Future research should consider social dynamics and psychological safety, use mixed methods for deeper insights and consider diverse cobots and tasks to expand decision-making studies. Emerging XR technologies offer the potential to enhance interaction and thus improve decision making, underscoring the need for intuitive communication and human-centred design.

18 May 2020 in Environment and Planning B: Urban Analytics and City Science
Verified
Journal Article
Closed access
PDF file
CPChristopher Pettit
Christopher Pettit
YSY Shi
Y Shi
Hoon HanHoon Han
Hoon Han
MRMarkus Rittenbruch
Markus Rittenbruch
Marcus FothMarcus Foth
Marcus Foth
MJM Jamal
M Jamal
In the digital era of big data, data analytics and smart cities, a new generation of planning support systems is emerging. The Rapid Analytics Interactive Scenario Explorer is a novel planning support system developed to help planners and policy-makers determine the likely land value uplift associated with the provision of new city infrastructure. The Rapid Analytics Interactive Scenario Explorer toolkit was developed following a user-centred research approach including iterative design, prototyping and evaluation. Tool development was informed by user inputs obtained through a series of co-design workshops with two end-user groups: land valuers and urban planners. The paper outlines the underlying technical architecture of the toolkit, which has the ability to perform rapid calculations and visualise the results, for the end-users, through an online mapping interface. The toolkit incorporates an ensemble of hedonic pricing models to calculate and visualise value uplift and so enable the user to explore what if? scenarios. The toolkit has been validated through an iterative case study approach. Use cases were related to two policy areas: property and land valuation processes (for land taxation purposes) and value uplift scenarios (for value capture purposes). The cases tested were in Western Sydney, Australia. The paper reports on the results of the ordinary least square linear regressions – used to explore the impacts of hedonic attributes on property value at the global level – and geographically weighted regressions – developed to provide local estimates and explore the varying spatial relationships between attributes and house price across the study area. Building upon the hedonic modelling, the paper also reports the value uplift functionality of the Rapid Analytics Interactive Scenario Explorer toolkit that enables users to drag and drop new train stations and rapidly calculate expected property prices under a range of future transport scenarios. The Rapid Analytics Interactive Scenario Explorer toolkit is believed to be the first of its kind to provide this specific functionality. As it is problem and policy specific, it can be considered an example of the next generation of data-driven planning support system.

5 December 2016 in Public Transport
Verified
Journal Article
Closed access
PDF file
TCTiago Camacho
Tiago Camacho
Marcus FothMarcus Foth
Marcus Foth
ARAndry Rakotonirainy
Andry Rakotonirainy
MRMarkus Rittenbruch
Markus Rittenbruch
Jonathan M BunkerJonathan M Bunker
Jonathan M Bunker

6 October 2013
Verified
Conference Paper
Open access
MRMarkus Rittenbruch
Markus Rittenbruch
ASAndrew Sorensen
Andrew Sorensen
JDJared Donovan
Jared Donovan
DPDebra Polson
Debra Polson
MDMichael Docherty
Michael Docherty
JJJeff Jones
Jeff Jones
“The Cube” is a unique facility that combines 48 large multi-touch screens and very large-scale projection surfaces to form one of the world’s largest interactive learning and engagement spaces. The Cube facility is part of the Queensland University of Technology’s (QUT) newly established Science and Engineering Centre, designed to showcase QUT’s teaching and research capabilities in the STEM (Science, Technology, Engineering, and Mathematics) disciplines. In this application paper we describe, the Cube, its technical capabilities, design rationale and practical day-to-day operations, supporting up to 70,000 visitors per week. Essential to the Cube’s operation are five interactive applications designed and developed in tandem with the Cube’s technical infrastructure. Each of the Cube’s launch applications was designed and delivered by an independent team, while the overall vision of the Cube was shepherded by a small executive team. The diversity of design, implementation and integration approaches pursued by these five teams provides some insight into the challenges, and opportunities, presented when working with large distributed interaction technologies. We describe each of these applications in order to discuss the different challenges and user needs they address, which types of interactions they support and how they utilise the capabilities of the Cube facility