Select Publications

Book Chapters

Abpeikar S; Kasmarik K; Tran PV; Garratt M; Anavatti S; Khan M, 2022, 'Chapter 8 Tuning swarm behavior for environmental sensing tasks represented as coverage problems', in Artificial Intelligence and Data Science in Environmental Sensing, Elsevier, pp. 155 - 178, http://dx.doi.org/10.1016/b978-0-323-90508-4.00001-0

Liu J; Anavatti S; Garratt M; Abbass HA, 2021, 'Marriage in Honey Bees Optimization in Continuous Domains', in Handbook of AI-based Metaheuristics, CRC Press, pp. 43 - 72, http://dx.doi.org/10.1201/9781003162841-4

Nguyen H; Garratt M; Abbass H, 2021, 'Apprenticeship Bootstrapping Reinforcement Learning for Sky Shepherding of a Ground Swarm in Gazebo', in Shepherding UxVs for Human-Swarm Teaming An Artificial Intelligence Approach to Unmanned X Vehicles, Springer Nature, pp. 207 - 243, http://dx.doi.org/10.1007/978-3-030-60898-9_10

Fernandez Rojas R; Debie E; fidock J; Barlow M; Kasmarik K; Anavatti S; Garratt M; Abbass H, 2021, 'Human Performance Operating Picture for Shepherding a Swarm of Autonomous Vehicles', in Shepherding UxVs for Human-Swarm Teaming An Artificial Intelligence Approach to Unmanned X Vehicles, Springer Nature, pp. 293 - 323, http://dx.doi.org/10.1007/978-3-030-60898-9_13

Liu J; Garratt M; Anavatti S; Abbass H, 2021, 'Mission Planning for Shepherding a Swarm of Uninhabited Aerial Vehicles', in Shepherding UxVs for Human-Swarm Teaming An Artificial Intelligence Approach to Unmanned X Vehicles, Springer Nature, pp. 87 - 114, http://dx.doi.org/10.1007/978-3-030-60898-9_5

Long N; Garratt M; sammut K; sgarioto D; Abbass H, 2021, 'Shepherding Autonomous Goal-Focused Swarms in Unknown Environments Using Hilbert Space-Filling Paths', in Shepherding UxVs for Human-Swarm Teaming An Artificial Intelligence Approach to Unmanned X Vehicles, Springer Nature, pp. 31 - 50, http://dx.doi.org/10.1007/978-3-030-60898-9_2

Baxter D; Garratt M; Abbass H, 2021, 'Simulating Single and Multiple Sheepdogs Guidance of a Sheep Swarm', in Shepherding UxVs for Human-Swarm Teaming An Artificial Intelligence Approach to Unmanned X Vehicles, Springer Nature, pp. 51 - 65, http://dx.doi.org/10.1007/978-3-030-60898-9_3

Debie E; Fernandez Rojas R; fidock J; Barlow M; Kasmarik K; Anavatti S; Garratt M; Abbass H, 2021, 'Transparent Shepherding: A Rule-Based Learning Shepherd for Human Swarm Teaming', in Shepherding UxVs for Human-Swarm Teaming An Artificial Intelligence Approach to Unmanned X Vehicles, Springer Nature, pp. 267 - 292, http://dx.doi.org/10.1007/978-3-030-60898-9_12

Santoso F; Garratt M; Anavatti S; Wang J, 2021, 'Evolutionary aerial robotics: the human way of learning', in Unmanned Aerial Systems Theoretical Foundation and Applications, Academic Press, pp. 1 - 23, http://dx.doi.org/10.1016/B978-0-12-820276-0.00008-X

Biswas S; Anavatti S; Garratt M, 2021, 'Path planning and task assignment for multiple UAVs in dynamic environments', in Unmanned Aerial Systems Theoretical Foundation and Applications, Academic Press, pp. 81 - 102, http://dx.doi.org/10.1016/B978-0-12-820276-0.00011-X

Santoso F; Garratt MA; Anavatti SG; Wang J, 2021, 'Evolutionary aerial robotics: the human way of learning', in Unmanned Aerial Systems: Theoretical Foundation and Applications, pp. 1 - 23, http://dx.doi.org/10.1016/b978-0-12-820276-0.00008-x

Al-Mahturi A; Santoso F; Garratt MA; Anavatti SG, 2021, 'Modeling and control of a quadrotor unmanned aerial vehicle using type-2 fuzzy systems', in Unmanned Aerial Systems: Theoretical Foundation and Applications, pp. 25 - 46, http://dx.doi.org/10.1016/b978-0-12-820276-0.00009-1

Biswas S; Anavatti SG; Garratt MA, 2021, 'Path planning and task assignment for multiple UAVs in dynamic environments', in Unmanned Aerial Systems: Theoretical Foundation and Applications, pp. 81 - 102, http://dx.doi.org/10.1016/b978-0-12-820276-0.00011-x

Francis S; Anavatti SG; Garratt M; Abbass HA, 2021, 'Real-Time Multi-obstacle Detection and Tracking Using a Vision Sensor for Autonomous Vehicle', in Communication and Intelligent Systems, Springer Singapore, pp. 873 - 883, http://dx.doi.org/10.1007/978-981-16-1089-9_67

Abpeikar S; Kasmarik K; Tran P; Garratt M; Anavatti S; Khan M, 2021, 'Tuning Swarm Behaviour for Environmental Sensing Tasks Represented as Coverage Problems', in Artificial Intelligence and Data Science in Environmental Sensing, pp. 155 - 178, http://dx.doi.org/10.1016/B978-0-323-90508-4.00001-0

Tran V; Santoso F; Garratt M, 2020, 'A Fuzzy Logic-Based Adaptive Strictly Negative-Imaginary Formation Controller for Multi-Quadrotor Systems', in Qian D (ed.), A Closer Look at Formation Control, Nova Science Publisher, New York, USA, https://novapublishers.com/shop/a-closer-look-at-formation-control/

Al-Mahasneh AJ; Anavatti S; Garratt M; Pratama M, 2018, 'Applications of General Regression Neural Networks in Dynamic Systems', in Digital Systems, pp. 133 - 154, http://dx.doi.org/10.5772/intechopen.80258

Santoso F; Garratt M; Anavatti S, 2018, 'Fuzzy Systems for Modelling and Control in Aerial Robotics', in Er MJ; Wang N; Zhichao L; Pratama M (ed.), Intelligent Marine Vehicles Theory and Applications, Nova Science Publisher, New York, https://www.novapublishers.com/catalog/product_info.php?products_id=64339

Biswas S; Anavatti S; Garratt M, 2017, 'Obstacle Avoidance for Multi-agent Path Planning Based on Vectorized Particle Swarm Optimization', in Leu G; Singh HK; Elsayed S (ed.), Intelligent and Evolutionary Systems. Proceedings in Adaptation, Learning and Optimization 8, edn. Proceedings in Adaptation Learning and Optimization, © Springer International Publishing, Univ New S Wales, Canberra Campus, Australian Def Force Acad, Canberra, AUSTRALIA, pp. 61 - 74, http://dx.doi.org/10.1007/978-3-319-49049-6_5

Francis SLX; anavatti S; garratt M, 2013, 'Model based path planning module', in Sen Gupta G; Bailey D; Demidenko S; Carnegie D (ed.), Recent Advances in Robotics and automation, Springer-Verlag, Berlin Heidelberg, pp. 81 - 90, http://dx.doi.org/10.1007/978-3-642-37387-9_6

Yang X; Garratt M; Pota H, 2010, 'Monotonous Trend Estimation of Deck Displacement for Automatic Landing of Rotorcraft UAVs', in Unmanned Aerial Vehicles, Springer Netherlands, pp. 267 - 285, http://dx.doi.org/10.1007/978-94-007-1110-5_18

Journal articles

Tran VP; Garratt MA; Kasmarik K; Anavatti SG; Leong AS; Zamani M, 2023, 'Multi-gas source localization and mapping by flocking robots', Information Fusion, vol. 91, pp. 665 - 680, http://dx.doi.org/10.1016/j.inffus.2022.11.001

Dong X; Garratt MA; Anavatti SG; Abbass HA, 2022, 'MobileXNet: An Efficient Convolutional Neural Network for Monocular Depth Estimation', IEEE Transactions on Intelligent Transportation Systems, vol. 23, pp. 20134 - 20147, http://dx.doi.org/10.1109/TITS.2022.3179365

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', Applied Ocean Research, vol. 127, pp. 103320 - 103320, http://dx.doi.org/10.1016/j.apor.2022.103320

Dong X; Garratt MA; Anavatti SG; Abbass HA, 2022, 'Towards Real-Time Monocular Depth Estimation for Robotics: A Survey', IEEE Transactions on Intelligent Transportation Systems, vol. 23, pp. 16940 - 16961, http://dx.doi.org/10.1109/TITS.2022.3160741

Liu J; Anavatti S; Garratt M; Abbass HA, 2022, 'Modified continuous Ant Colony Optimisation for multiple Unmanned Ground Vehicle path planning', Expert Systems with Applications, vol. 196, pp. 116605 - 116605, http://dx.doi.org/10.1016/j.eswa.2022.116605

Liu J; Anavatti S; Garratt M; Tan KC; Abbass HA, 2022, 'A survey, taxonomy and progress evaluation of three decades of swarm optimisation', Artificial Intelligence Review, vol. 55, pp. 3607 - 3725, http://dx.doi.org/10.1007/s10462-021-10095-z

Rajamohan D; Kim J; Garratt M; Pickering M, 2022, 'Image based Localization under large perspective difference between Sfm and SLAM using split sim(3) optimization', Autonomous Robots, vol. 46, pp. 437 - 449, http://dx.doi.org/10.1007/s10514-021-10031-8

Liu J; Anavatti S; Garratt M; Abbass HA, 2022, 'Multi-operator continuous ant colony optimisation for real world problems', Swarm and Evolutionary Computation, vol. 69, pp. 100984 - 100984, http://dx.doi.org/10.1016/j.swevo.2021.100984

Al-Mahasneh AJ; Anavatti SG; Garratt MA, 2022, 'Online Model-Free Reinforcement Learning for Output Feedback Tracking Control of a Class of Discrete-Time Systems with Input Saturation', IEEE Access, vol. 10, pp. 104966 - 104979, http://dx.doi.org/10.1109/ACCESS.2022.3210136

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', IEEE Transactions on Cybernetics, http://dx.doi.org/10.1109/TCYB.2022.3175366

Abpeikar S; Kasmarik K; Garratt M; Hunjet R; Khan M; Qiu H, 2022, 'Automatic Collective Motion Tuning using Actor-Critic Deep Reinforcement Learning', Swarm and Evolutionary Computation, vol. 72, http://dx.doi.org/10.1016/j.swevo.2022.101085

Tran P; Abpeikar S; Kasmarik K; Garratt M; Anavatti S, 2022, 'Frontier Led Swarming: Robust Multi-robot coverage of Unknown Environments', Swarm and Evolutionary Computation

Tran VP; Santoso F; Garratt MA; Petersen IR, 2021, 'Distributed Formation Control Using Fuzzy Self-Tuning of Strictly Negative Imaginary Consensus Controllers in Aerial Robotics', IEEE/ASME Transactions on Mechatronics, vol. 26, pp. 2306 - 2315, http://dx.doi.org/10.1109/TMECH.2020.3036829

Tran VP; Santoso F; Garratt MA, 2021, 'Adaptive Trajectory Tracking for Quadrotor Systems in Unknown Wind Environments Using Particle Swarm Optimization-Based Strictly Negative Imaginary Controllers', IEEE Transactions on Aerospace and Electronic Systems, vol. 57, pp. 1742 - 1752, http://dx.doi.org/10.1109/TAES.2020.3048778

Tran VP; Mabrok MA; Garratt MA; Petersen IR, 2021, 'Hybrid adaptive negative imaginary- neural-fuzzy control with model identification for a quadrotor', IFAC Journal of Systems and Control, vol. 16, http://dx.doi.org/10.1016/j.ifacsc.2021.100156

Al-Mahasneh AJ; Anavatti SG; Garratt MA; Pratama M, 2021, 'Stable Adaptive Controller Based on Generalized Regression Neural Networks and Sliding Mode Control for a Class of Nonlinear Time-Varying Systems', IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 51, pp. 2525 - 2535, http://dx.doi.org/10.1109/TSMC.2019.2915950

Tran VP; Garratt MA; Petersen IR, 2021, 'Multi-vehicle formation control and obstacle avoidance using negative-imaginary systems theory', IFAC Journal of Systems and Control, vol. 15, http://dx.doi.org/10.1016/j.ifacsc.2020.100117

Biswas S; Anavatti SG; Garratt MA, 2021, 'Multiobjective Mission Route Planning Problem: A Neural Network-Based Forecasting Model for Mission Planning', IEEE Transactions on Intelligent Transportation Systems, vol. 22, pp. 430 - 442, http://dx.doi.org/10.1109/TITS.2019.2960057

Muthusamy PK; Garratt M; Pota HR; Muthusamy R, 2021, 'Realtime Adaptive Intelligent Control System for Quadcopter UAV with Payload Uncertainties', IEEE Transactions on Industrial Electronics, pp. 1 - 1, http://dx.doi.org/10.1109/TIE.2021.3055170

Al-Mahturi A; Santoso F; Garratt MA; Anavatti SG, 2021, 'Self-Learning in Aerial Robotics Using Type-2 Fuzzy Systems: Case Study in Hovering Quadrotor Flight Control', IEEE Access, vol. 9, pp. 119520 - 119532, http://dx.doi.org/10.1109/ACCESS.2021.3107906

Debie E; El-Fiqi H; Fidock J; Barlow M; Kasmarik K; Anavatti S; Garratt M; Abbass H, 2021, 'Autonomous recommender system for reconnaissance tasks using a swarm of UAVs and asynchronous shepherding', Human-Intelligent Systems Integration, vol. 3, pp. 175 - 186, http://dx.doi.org/10.1007/s42454-020-00024-w

Tran VP; Garratt MA; Petersen IR, 2020, 'Switching formation strategy with the directed dynamic topology for collision avoidance of a multi-robot system in uncertain environments', IET Control Theory and Applications, vol. 14, pp. 2948 - 2959, http://dx.doi.org/10.1049/iet-cta.2020.0502

Al-Mahasneh AJ; Anavatti SG; Garratt MA, 2020, 'Self-Evolving Neural Control for a Class of Nonlinear Discrete-Time Dynamic Systems with Unknown Dynamics and Unknown Disturbances', IEEE Transactions on Industrial Informatics, vol. 16, pp. 6518 - 6529, http://dx.doi.org/10.1109/TII.2019.2958381

Long NK; Sammut K; Sgarioto D; Garratt M; Abbass HA, 2020, 'A Comprehensive review of shepherding as a bio-inspired swarm-robotics guidance approach', IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 4, pp. 523 - 537, http://dx.doi.org/10.1109/TETCI.2020.2992778

Ferdaus MM; Pratama M; Anavatti SG; Garratt MA; Pan Y, 2020, 'Generic Evolving Self-Organizing Neuro-Fuzzy Control of Bio-Inspired Unmanned Aerial Vehicles', IEEE Transactions on Fuzzy Systems, vol. 28, pp. 1542 - 1556, http://dx.doi.org/10.1109/TFUZZ.2019.2917808

Santoso F; Garratt MA; Anavatti SG; Petersen I, 2020, 'Robust Hybrid Nonlinear Control Systems for the Dynamics of a Quadcopter Drone', IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 50, pp. 3059 - 3071, http://dx.doi.org/10.1109/TSMC.2018.2836922

Young J; Garratt M, 2020, 'Drones become even more insect-like', Science, vol. 368, pp. 586 - 587, http://dx.doi.org/10.1126/science.abb0064

Fernandez Rojas R; Debie E; Fidock J; Barlow M; Kasmarik K; Anavatti S; Garratt M; Abbass H, 2020, 'Electroencephalographic Workload Indicators During Teleoperation of an Unmanned Aerial Vehicle Shepherding a Swarm of Unmanned Ground Vehicles in Contested Environments', Frontiers in Neuroscience, vol. 14, http://dx.doi.org/10.3389/fnins.2020.00040

Ferdaus MM; Pratama M; Anavatti SG; Garratt MA; Lughofer E, 2020, 'PAC: A novel self-adaptive neuro-fuzzy controller for micro aerial vehicles', Information Sciences, vol. 512, pp. 481 - 505, http://dx.doi.org/10.1016/j.ins.2019.10.001


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