Profiles

Robert Ollington

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Robert Ollington

Lecturer
Information & Communication Technology

Centenary Building , Sandy Bay Campus

+61 3 6226 2991 (phone)

Robert.Ollington@utas.edu.au

View more on Dr Robert Ollington in WARP

Fields of Research

  • Neural networks (461104)
  • Intelligent robotics (460205)
  • Artificial life and complex adaptive systems (460201)
  • Computer vision (460304)
  • Image processing (460306)
  • Natural language processing (460208)
  • Analog electronics and interfaces (400901)
  • Artificial intelligence (460299)
  • Clinical pharmacy and pharmacy practice (321403)
  • Computer graphics (460702)
  • Pattern recognition (460308)

Research Objectives

  • Other information and communication services (229999)
  • Expanding knowledge in the information and computing sciences (280115)
  • Artificial intelligence (220403)
  • Expanding knowledge in the mathematical sciences (280118)
  • Measurement and assessment of freshwater quality (incl. physical and chemical conditions of water) (180306)
  • Processed fish and seafood products (241310)
  • Teaching and instruction technologies (160304)
  • Environmentally sustainable information and communication services (220299)
  • Oceanic processes (excl. in the Antarctic and Southern Ocean) (180506)
  • Assessment and management of benthic marine ecosystems (180501)
  • Expanding knowledge in the chemical sciences (280105)
  • Road infrastructure and networks (270308)
  • Expanding knowledge in psychology (280121)
  • Command, control and communications (140102)
  • Road safety (270311)

Publications

Total publications

22

Journal Article

(8 outputs)
YearCitationAltmetrics
2021Mohawesh R, Tran S, Ollington R, Xu S, 'Analysis of concept drift in fake reviews detection', Expert Systems with Applications, 169 Article 114318. ISSN 0957-4174 (2021) [Refereed Article]

DOI: 10.1016/j.eswa.2020.114318 [eCite] [Details]

Citations: Scopus - 1

Co-authors: Mohawesh R; Tran S; Xu S

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2021Mohawesh R, Xu S, Tran SN, Ollington R, Springer M, et al., 'Fake reviews detection: A survey', IEEE Access, 9 pp. 65771-65802. ISSN 2169-3536 (2021) [Refereed Article]

DOI: 10.1109/ACCESS.2021.3075573 [eCite] [Details]

Co-authors: Mohawesh R; Xu S; Tran SN; Springer M

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2020Vo SA, Scanlan J, Turner P, Ollington R, 'Convolutional Neural Networks for individual identification in the Southern Rock Lobster supply chain', Food Control, 118 Article 107419. ISSN 0956-7135 (2020) [Refereed Article]

DOI: 10.1016/j.foodcont.2020.107419 [eCite] [Details]

Citations: Scopus - 1Web of Science - 1

Co-authors: Vo SA; Scanlan J; Turner P

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2016Pentecost D, Sennersten C, Ollington R, Lindley C, Kang B, 'Using a physics engine in ACT-R to aid decision making', International Journal on Advances in Intelligent Systems, 9, (3-4) pp. 298-309. ISSN 1942-2679 (2016) [Professional, Refereed Article]

[eCite] [Details]

Co-authors: Pentecost D; Kang B

2014Bindoff I, Ling T, Bereznicki L, Westbury J, Chalmers L, et al., 'A computer simulation of community pharmacy practice for educational use', American Journal of Pharmaceutical Education, 78, (9) Article 168. ISSN 0002-9459 (2014) [Refereed Article]

DOI: 10.5688/ajpe789168 [eCite] [Details]

Citations: Web of Science - 17

Co-authors: Bindoff I; Ling T; Bereznicki L; Westbury J; Chalmers L; Peterson G

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2011Breen J, de Souza P, Timms GP, Ollington R, 'Onboard assessment of XRF spectra using genetic algorithms for decision making on an autonomous underwater vehicle', Nuclear Instruments and Methods in Physics Research. Section B. Beam Interactions With Materials and Atoms, 269, (12) pp. 1341-1345. ISSN 0168-583X (2011) [Refereed Article]

DOI: 10.1016/j.nimb.2011.03.012 [eCite] [Details]

Citations: Scopus - 7Web of Science - 7

Co-authors: de Souza P

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2005Ollington RB, Vamplew PW, 'Concurrent Q-Learning: Reinforcement Learning for Dynamic Goals and Environments', International Journal of Intelligent Systems, 20, (10) pp. 1037-1052. ISSN 0884-8173 (2005) [Refereed Article]

DOI: 10.1002/int.20105 [eCite] [Details]

Citations: Scopus - 10Web of Science - 8

Co-authors: Vamplew PW

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2001Ollington RB, Vamplew PW, 'A Supervised Neural Network Based on the Cerebellum', Australian Journal of Intelligent Information Processing Systems, 6, (4) pp. 242-274. ISSN 1321-2133 (2001) [Refereed Article]

[eCite] [Details]

Co-authors: Vamplew PW

Chapter in Book

(1 outputs)
YearCitationAltmetrics
2009Ollington RB, Vamplew PH, Swanson J, 'Incorporating expert advice into reinforcement learning using constructive neural networks', Constructive Neural Networks, Springer, Leonardo Franco, David A Elizondo and Jose M Jerez (ed), Berlin, Heidelberg, pp. 207-224. ISBN 978-3-642-04511-0 (2009) [Research Book Chapter]

DOI: 10.1007/978-3-642-04512-7_11 [eCite] [Details]

Citations: Scopus - 1

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Conference Publication

(13 outputs)
YearCitationAltmetrics
2016Grace A, Ollington R, Lewis I, 'Accurate image-space environment reflections in real-time', Proceedings of the 9th Annual International Conference on Computer Games Multimedia & Allied Technologies (CGAT 2016), 28-29 March 2016, Singapore, pp. 1-8. (2016) [Refereed Conference Paper]

DOI: 10.5176/2251-1679_CGAT16.3 [eCite] [Details]

Co-authors: Grace A; Lewis I

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2016McClarron P, Ollington R, Lewis I, 'Effect of constraints on evolving behavior trees for game AI', Proceedings of the 9th Annual International Conference on Computer Games Multimedia & Allied Technologies (CGAT 2016), 28-29 March 2016, Singapore, pp. 1-6. ISSN 2251-1679 (2016) [Refereed Conference Paper]

DOI: 10.5176/2251-1679_CGAT16.2 [eCite] [Details]

Co-authors: McClarron P; Lewis I

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2016Pentecost D, Sennersten C, Ollington R, Lindley CA, Kang B, 'Predictive ACT-R (PACT-R): Using a physics engine and simulation for physical prediction in a cognitive architecture', Proceedings of the 8th International Conference on Advanced Cognitive Technologies and Applications (COGNITIVE 2016), 20-24 March 2016, Rome, Italy, pp. 22-32. ISBN 978-1-61208-462-6 (2016) [Refereed Conference Paper]

[eCite] [Details]

Co-authors: Pentecost D; Kang B

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2013Cohen WJ, Ollington RB, Ling FLN, 'Hydrologic model parameter optimisation', Proceedings of the 20th International Congress on Modelling and Simulation (MODSIM 2013), 1-6 December 2013, Adelaide, Australia, pp. 1-7. ISBN 978-0-9872143-2-4 (2013) [Refereed Conference Paper]

[eCite] [Details]

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2013Jackett CJ, Ollington R, Lovell JL, 'Efficient digital FFT convolution with boundary kernel renormalisation', Proceedings of the International Conference on Digital Image Computing: Techniques and Applications (DICTA-13), 26-28 November 2013, Hobart, Australia, pp. 1-6. ISBN 978-1-4799-2126-3 (2013) [Refereed Conference Paper]

DOI: 10.1109/DICTA.2013.6691496 [eCite] [Details]

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2012Breen JP, de Souza P, Timms G, Mculloch J, Ollington RB, 'Analysis of Heavy Metals in Marine Sediment using a Portable X-ray Fluorescence Spectrometer Onboard an Autonomous Underwater Vehicle', Proceedings - Oceans 2012, 21-24 May 2012, Yeosu, KOREA EJ ISBN 978-1-4577-2090-1 (2012) [Non Refereed Conference Paper]

DOI: 10.1109/OCEANS-Yeosu.2012.6263419 [eCite] [Details]

Citations: Scopus - 2

Co-authors: de Souza P

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2006Vamplew PW, Ollington RB, Hepburn M, 'Enhanced Temporal Difference Learning Using Compiled Eligibility Traces', AI 2006: Advances in Artificial Intelligence 19th Australian Joint Conference on Artificial Intelligence, 4-8 December, 2006, Hobart, Tasmania, pp. 141-150. ISBN 3-540-49787-0 (2006) [Refereed Conference Paper]

[eCite] [Details]

Co-authors: Hepburn M

2005Vamplew PW, Ollington RB, 'On-Line Reinforcement Learning Using Cascade Constructive Neural Networks', Knowledge-based intelligent information and engineering systems : 9th international conference : proceedings, September 2005, Melbourne, pp. 562-568. ISBN 3-540-28896-1 (2005) [Refereed Conference Paper]

[eCite] [Details]

Co-authors: Vamplew PW

2005Vamplew PW, Ollington RB, 'Global Versus Local Constructive Function Approximation for On-Line Reinforcement Learning', AI 2005 : advances in artificial intelligence : 18th Australian Joint Conference on Artificial Intelligence, December 2005, Sydney, pp. 113-122. ISBN 3-540-30462-2 (2005) [Refereed Conference Paper]

[eCite] [Details]

Co-authors: Vamplew PW

2004Ollington RB, Vamplew PW, 'Learning Place Cells from Sonar data', Proceedings AISAT 2004 The 2nd International Conference on Artificial Intelligence in Science and Technology, 21-25 November 2004, Hobart, Tasmania, pp. 126-131. ISBN 1 86295 209 4 (2004) [Refereed Conference Paper]

[eCite] [Details]

Co-authors: Vamplew PW

2004Ollington RB, Vamplew PW, 'Reducing the Time Complexity of Goal-Independent Reinforcement Learning', Proceedings AISAT 2004 The 2nd International Conference on Artificial Intelligence in Science and Technology, 21-25 November 2004, Hobart, Tasmania, pp. 132-137. ISBN 1 86295 209 4 (2004) [Refereed Conference Paper]

[eCite] [Details]

Co-authors: Vamplew PW

2003Ollington RB, Vamplew PW, 'Concurrent Q-Learning for Autonomous Mapping and Navigation', The Second International Conference on Computational Intelligence, Robotics and Autononymous Systems, 15-18 December 2003, Singapore EJ ISSN 0219-6131 (2003) [Refereed Conference Paper]

[eCite] [Details]

Co-authors: Vamplew PW

2003Ollington RB, Vamplew PW, 'Adaptive Response Function Neurons', The Second International Conference on Computational Intelligence, Robotics and Autononymous Systems, 15-18 December 2003, Singapore EJ ISSN 0219-6131 (2003) [Refereed Conference Paper]

[eCite] [Details]

Co-authors: Vamplew PW

Grants & Funding

Funding Summary

Number of grants

2

Total funding

$270,363

Projects

A Low Cost, Automated Data Collection and Defect Detection System for Paved Roads (2020 - 2023)$161,280
Description
Road networks play a crucial role in socioeconomic and regional development. Due to the rapid development of automobile manufacturing in the 20th century, individual transportation became available to the masses, as a result, the road networks experienced a rapid increase in usage. To assure ride safety the road networks need to be maintained at a desirable level.To maintain at a desirable level, roads are monitored by surveyors to capture the longitudinal and transverse profiles, and the condition of surface and edges. If detected, surface defects are assessed and if possible are either addressed on the spot or are assigned a priority rating for repair work. Clearly, such manual surveys are inherently inefficient, laborious and time-consuming.Therefore, there is need for a low cost road surface defect detection system that will be used frequently for not only the highways but also for the remaining part of the road network that often remains unattended due to high cost of the current solutions.The aim of this project is to develop an automated data collection and defect detection system for paved roads that has a low purchase, maintenance and operational cost.
Funding
ISW PTY LTD ($161,280)
Scheme
Contract Research
Administered By
University of Tasmania
Research Team
Ollington RB; Kang BH; Park M; Cao Z
Period
2020 - 2023
Design of communication gateways for micro-sensing devices deployable on insects (2014 - 2016)$109,083
Description
This project will focus on exploring, designing and implementing communication solutions for micro-sensing devices, considering tight energy budgets. The possible communication solutions could include radio-frequency identification (RFIOs), radio in the VHF range, light (laser, LEOs), as well as high-GHz to THz range waves (Mom2011 ), (f\br2003]. To increase the effective communication reach of these devices, mobile receivers will be deployed on aerial robots (drones). Furthermore, the drones could acquire additional data along the insect's flight path, like local temperature, lighting, and (multispectral) imaging data. The key Fundamental Science questions are: (1) How accurately can micro-sensing devices be tracked in the field? (2) Is it possible to efficiently build an ad-hoc network of micro-sensing devices? What are the real benefits of this approach of sensor-sensor communication? (3) How to deal with loss of sensors and/or data gaps over time? Miniaturised electronics has enabled a number of applications such as tracking and tagging to emerge. However, sensing at the sub-mm scale has not been become possible mainly because of energy and communication constraints. The significance of this project lies in: (1) deploying not only a couple, but dozens of RFIDs in a swarm of insects to gain understanding of their behaviour; (2) designing communication solutions for sub-mm sensing devices advancing further than current commercially available alternatives; (3) exploring sensor-sensor communication in a sub-mm sensor network. This research project will deliver unprecedented data on both insect behaviour and on microclimate and, furthermore, on their relationships.
Funding
CSIRO-Commonwealth Scientific & Industrial Research Organisation ($109,083)
Scheme
Grant-Flagship Project [Unsolicited]
Administered By
University of Tasmania
Research Team
de Souza Junior P; Ollington RB; Allen GR; Lucieer A
Period
2014 - 2016

Research Supervision

Current

7

Completed

4

Current

DegreeTitleCommenced
PhDAgent Dynamics in a Topological Space: Computational learning of agent dynamics using game theory topology and reinforcement learning2018
PhDFuture of Officials in Modern Day Cricket2019
PhDMachine Learning Approach for Sentiment Analysis (or Opinion Mining)2019
PhDPrivacy in a Smart City2019
PhDAnomaly Detection for Transport Infrastructure2020
PhDAI and Learning: Temporary emotion and performance in learning2020
MastersOpen Set Deep Learning Model for Image Classification2021

Completed

DegreeTitleCompleted
PhDDesign of Communication Gateways for Micro-Sensing Devices Deployable on Insects
Candidate: Pascal Hirsch
2019
PhDBenthic Habitat Mapping by Autonomous Underwater Vehicles
Candidate: Andrew Davie
2013
PhDDeconvolving and Improving the Spatial Resolution of Satellite Data using the Maximum Entropy Method
Candidate: Christopher James Jackett
2013
PhDChemical Analysis of Sediments Using X-Ray Fluorescence On-board an Autonomous Underwater Vehicle
Candidate: Jeremy Peter Breen
2013