By Professor Matt Garratt

Conference Papers

Garratt MA; Pota HR; Lambert AJ; Eckersley-Maslin SJ, 2007, 'Systems for automated launch and recovery of an unmanned aerial vehicle from ships at sea', in 22nd International UAV Systems Conference, Bristol, UK, presented at 22nd International UAV Systems Conference, Bristol, UK, 16 April 2007 - 18 April 2007

Pota HR; Garratt MA; Ahmed B, 2006, 'Velocity Control of a UAV using Backstepping Control', in 45th IEEE Conference on Decision and Control, San Diego, Californa, USA, presented at 45th IEEE Conference on Decision and Control, San Diego, Californa, USA, 13 December 2006 - 15 December 2006

Garratt MA; Ahmed B; Pota HR, 2006, 'Platform Enhancements and system identification for control of an unmanned helicopter', in 2006 9th International Conference on Control, Automation, Robotics and Vision, Singapore, presented at 9th International Conference on Control, Automation, Robotics and Vision 2006, Singapore, 05 December 2006 - 08 December 2006

Pota HR; Garratt MA; Oh S; Pathak K; Agrawal SK, 2005, 'Autonomous Helicopter Landing on a moving Platform Using a Tether', in 2005 IEEE international Conference on Robotics and Automation, Barcelona, Spain, presented at IEEE international Conference on Robotics and Automation 2005, Barcelona, Spain, 18 April 2005 - 22 April 2005

Soccol DD; Chahl JS; Le Bouffant N; Garratt MA; Mizutani A; Thurrowgood SA; Ewyk G; Thakoor S, 2003, 'A utilitarian UAV design for NASA bioinspired flight control research', in 41st Aerospace Sciences Meeting and Exhibit

Garratt MA; Chahl JS, 2003, 'Visual control of an autonomous helicopter', in 41st Aerospace Sciences Meeting and Exhibit

Srinivasan MV; Zhang SW; Chahl JS; Garratt MA, 2001, 'Landing strategies in honeybees, and applications to UAVs', in Jarvis RA; Zelinsky A (ed.), ROBOTICS RESEARCH, SPRINGER-VERLAG BERLIN, AUSTRALIA, LORNE, pp. 373 - 384, presented at 10th International Symposium on Robotics Research (ISRR 2001), AUSTRALIA, LORNE, 09 November 2001 - 12 November 2001, https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000183013700024&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=891bb5ab6ba270e68a29b250adbe88d1

Conference Posters

Abpeikar S; Kasmarik K; Tran P; Garratt M, (eds.), 2022, 'Transfer Learning for Autonomous Recognition of Swarm Behaviour in UGVs', Sydney, Vol. 13151 LNAI, pp. 531 - 542, presented at Australian Joint Conference on Artificial Intelligence, Sydney, 02 February 2022 - 04 February 2022, http://dx.doi.org/10.1007/978-3-030-97546-3_43

Theses / Dissertations

Smith B, 2019, A Comprehensive Examination of Low Earth Orbit Aerodynamic Accelerations for Satellite Formation Control

Preprints

Rajbhandari P; Veda A; Garratt M; Srinivasan M; Ravi S, 2026, Understanding visual attention beehind bee-inspired UAV navigation, http://dx.doi.org/10.48550/arxiv.2507.11992

Hafeez H; Garratt M; Plested J; Iyer S; Sowmya A, 2025, YOLO11-4K: An Efficient Architecture for Real-Time Small Object Detection in 4K Panoramic Images, http://dx.doi.org/10.48550/arxiv.2512.16493

Tran VP; Perera AG; Garratt MA; Kasmarik K; Anavatti SG, 2024, Active Sensing Strategy: Multi-Modal, Multi-Robot Source Localization and Mapping in Real-World Settings with Fixed One-Way Switching, http://dx.doi.org/10.48550/arxiv.2407.01308

Perera A; Tran VP; Anavatti S; Kasmarik K; Garratt M, 2023, Radio Source Localization using Sparse Signal Measurements from Uncrewed Ground Vehicles, http://dx.doi.org/10.48550/arxiv.2312.03493

Francis S; Dam T; Anavatti S; Garratt MA, 2023, Adaptive Terrain Perception and Decision-Making Systems for Agile Mobile Robots in Dynamic Search and Rescue Scenarios, http://dx.doi.org/10.20944/preprints202310.0738.v1

Farlow H; Garratt M; Mount G; Lynar T, 2023, The race to robustness: exploiting fragile models for urban camouflage and the imperative for machine learning security, http://dx.doi.org/10.48550/arxiv.2306.14609

Tran VP; Perera A; Garratt MA; Kasmarik K; Anavatti S, 2023, Coverage Path Planning with Budget Constraints for Multiple Unmanned Ground Vehicles, http://dx.doi.org/10.48550/arxiv.2306.04083

Dong X; Garratt MA; Anavatti SG; Abbass HA; Dong J, 2022, Lightweight Monocular Depth Estimation with an Edge Guided Network, http://dx.doi.org/10.48550/arxiv.2209.14829

Long NK; Sgarioto D; Garratt M; Sammut K, 2022, Response Component Analysis for Sea State Estimation Using Artificial Neural Networks and Vessel Response Spectral Data, http://dx.doi.org/10.48550/arxiv.2205.02375

Tran VP; Mabrok MA; Anavatti SG; Garratt MA; Petersen IR, 2022, Robust Fuzzy Q-Learning-Based Strictly Negative Imaginary Tracking Controllers for the Uncertain Quadrotor Systems, http://dx.doi.org/10.48550/arxiv.2203.13959

Tran VP; Garratt MA; Kasmarik K; Anavatti SG, 2022, Frontier-led Swarming: Robust Multi-Robot Coverage of Unknown Environments, http://dx.doi.org/10.48550/arxiv.2111.14295

Dong X; Garratt MA; Anavatti SG; Abbass HA, 2021, MobileXNet: An Efficient Convolutional Neural Network for Monocular Depth Estimation, http://dx.doi.org/10.48550/arxiv.2111.12334

Dong X; Garratt MA; Anavatti SG; Abbass HA, 2021, Towards Real-Time Monocular Depth Estimation for Robotics: A Survey, http://dx.doi.org/10.48550/arxiv.2111.08600

Nguyen HT; Garratt M; Bui LT; Abbass H, 2020, Disturbances in Influence of a Shepherding Agent is More Impactful than Sensorial Noise During Swarm Guidance, http://dx.doi.org/10.48550/arxiv.2008.12708

Nguyen HT; Nguyen TD; Tran VP; Garratt M; Kasmarik K; Anavatti S; Barlow M; Abbass HA, 2020, Continuous Deep Hierarchical Reinforcement Learning for Ground-Air Swarm Shepherding, http://dx.doi.org/10.48550/arxiv.2004.11543

Qiu H; Garratt M; Howard D; Anavatti S, 2020, Towards Crossing the Reality Gap with Evolved Plastic Neurocontrollers, http://dx.doi.org/10.48550/arxiv.2002.09854

Long NK; Sammut K; Sgarioto D; Garratt M; Abbass H, 2020, A Comprehensive Review of Shepherding as a Bio-inspired Swarm-Robotics Guidance Approach, http://dx.doi.org/10.48550/arxiv.1912.07796

Ferdaus MM; Pratama M; Anavatti SG; Garratt MA; Lughofer E, 2019, PAC: A Novel Self-Adaptive Neuro-Fuzzy Controller for Micro Aerial Vehicles, http://dx.doi.org/10.48550/arxiv.1811.03764

Qiu H; Garratt M; Howard D; Anavatti S, 2019, Evolving Spiking Neural Networks for Nonlinear Control Problems, http://dx.doi.org/10.48550/arxiv.1903.01180

Tran VP; Garratt M; Petersen IR, 2018, Distributed Obstacle and Multi-Robot Collision Avoidance in Uncertain Environments, http://dx.doi.org/10.48550/arxiv.1811.06196

Tran VP; Garratt M; Petersen IR, 2018, Time-Varying Formation Control of a Collaborative Multi-Agent System Using Negative-Imaginary Systems Theory, http://dx.doi.org/10.48550/arxiv.1811.06206

Nguyen H; Tran V; Nguyen T; Garratt M; Kasmarik K; Barlow M; Anavatti S; Abbass H, 2018, Apprenticeship Bootstrapping Via Deep Learning with a Safety Net for UAV-UGV Interaction, http://dx.doi.org/10.48550/arxiv.1810.04344

Ferdaus MM; Pratama M; Anavatti SG; Garratt MA, 2018, PALM: An Incremental Construction of Hyperplanes for Data Stream Regression, http://dx.doi.org/10.48550/arxiv.1805.04258

Ferdaus MM; Anavatti SG; Garratt MA; Pratama M, 2018, Development of a Sliding Mode Control Based Adaptive Fuzzy Controller for a Flapping Flight, http://dx.doi.org/10.48550/arxiv.1806.02945

Al-Mahasneh AJ; Anavatti SG; Garratt MA, 2018, Review of Applications of Generalized Regression Neural Networks in Identification and Control of Dynamic Systems, http://dx.doi.org/10.48550/arxiv.1805.11236

Ferdaus MM; Pratama M; Anavatti SG; Garratt MA, 2018, A Generic Self-Evolving Neuro-Fuzzy Controller based High-performance Hexacopter Altitude Control System, http://dx.doi.org/10.48550/arxiv.1805.02508

Ferdaus MM; Anavatti SG; Garratt MA; Pratama M, 2018, Development of c-means Clustering Based Adaptive Fuzzy Controller for A Flapping Wing Micro Air Vehicle, http://dx.doi.org/10.48550/arxiv.1802.01262

Ferdaus MM; Pratama M; Anavatti SG; Garratt MA; Pan Y, 2018, Generic Evolving Self-Organizing Neuro-Fuzzy Control of Bio-inspired Unmanned Aerial Vehicles, http://dx.doi.org/10.48550/arxiv.1802.00635

Jakobi TR; Garratt M; Srinivasan MV; Ravi S, Threading the needle: Spatial constraints sharpen visual sensitivity in honeybees, http://dx.doi.org/10.64898/2026.01.02.696520

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