Book Chapters

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

Hassanein O; Anavatti S; Ray T, 2018, 'Autonomous Underwater Vehicles', in Meng Joo E (ed.), Intelligent Marine and Aerial Vehicles: Theory and Applications, Nova Publishers, https://novapublishers.com/shop/intelligent-marine-and-aerial-vehicles-theory-and-applications/

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

Anavatti SG; ray T, 2016, 'A Game-Theoretic Approach to the Analysis of Traffic Assignment', in singh H (ed.), Intelligent and Evolutionary Systems The 20th Asia Pacific Symposium, IES 2016, Canberra, Australia, November 2016, Proceedings, Springer, pp. 17 - 30, http://dx.doi.org/10.1007/978-3-319-49049-6_2

Anavatti SG; li C; ray T, 2016, 'A game-theoretic approach to the analysis of Traffic Assignment', in Intelligent and Evolutionary Systems The 20th Asia Pacific Symposium, IES 2016, Canberra, Australia, November 2016, Proceedings, Springer, pp. 17 - 30, http://dx.doi.org/10.1007/978-3-319-49049-6_2

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

Hassanein O; Anavatti SG; Ray T, 2013, 'On-line adaptive fuzzy modeling and control for autonomous underwater vehicle', in Recent Advances in Robotics and Automation, Springer, Heidelberg, pp. 57 - 70, http://dx.doi.org/10.1007/978-3-642-37387-9_4

Anavatti SG, 2012, 'An Evolutionary Approach for the Design of Autonomous Underwater Vehicles', in An Evolutionary Approach for the Design of Autonomous Underwater Vehicles, http://dx.doi.org/10.1007/978-3-642-35101-3_24

anavatti S, 2007, 'Comparative Analysis of Multiple Neural Networks for Online Identification of a UAV', in Comparative Analysis of Multiple Neural Networks for Online Identification of a UAV, http://link.springer.com/chapter/10.1007/978-3-540-76928-6_14

Anavatti SG; anavatti SG, 2007, 'Application of Extended Kalman Filter Towards UAV Identification', in Application of Extended Kalman Filter Towards UAV Identification, http://dx.doi.org/10.1007/978-3-540-73424-6_23

Journal articles

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

Ferdaus MM; Anavatti SG; Pratama M; Garratt MA, 2020, 'Towards the use of fuzzy logic systems in rotary wing unmanned aerial vehicle: a review', Artificial Intelligence Review, vol. 53, pp. 257 - 290, http://dx.doi.org/10.1007/s10462-018-9653-z

Santoso F; Garratt M; Anavatti S, 2019, 'Robust Hybrid Feedback Linearization and Interval Type-2 Fuzzy Control Systems for the Flapping Angle Dynamics of a Biomimetic Aircraft', IEEE Transactions on Systems Man and Cybernetics: Systems, http://dx.doi.org/10.1109/TSMC.2019.2956735

Santoso F; Garratt M; Anavatti S; Hasanein ; Stenhouse T, 2019, 'Entropy Fuzzy System Identification for the Heave Flight Dynamics of a Model-Scale Helicopter', IEEE-ASME Transactions on Mechatronics, http://dx.doi.org/10.1109/TMECH.2019.2959279

Ferdaus MM; Pratama M; Anavatti SG; Garratt MA, 2019, 'PALM: An Incremental Construction of Hyperplanes for Data Stream Regression', IEEE Transactions on Fuzzy Systems, vol. 27, pp. 2115 - 2129, http://dx.doi.org/10.1109/TFUZZ.2019.2893565

Santoso F; Garratt M; Anavatti S, 2019, 'T2-ETS-IE: Type-2 Evolutionary Takagi-Sugeno Fuzzy Inference Systems with the Information Entropy-Based Pruning Technique', IEEE Transactions on Fuzzy Systems, http://dx.doi.org/10.1109/TFUZZ.2019.2943813

Ferdaus MM; Anavatti SG; Garratt MA; Pratama M, 2019, 'Development of C-Means Clustering Based Adaptive Fuzzy Controller for a Flapping Wing Micro Air Vehicle', Journal of Artificial Intelligence and Soft Computing Research, vol. 9, pp. 99 - 109, http://dx.doi.org/10.2478/jaiscr-2018-0027

Santoso F; Garratt M; Anavatti S, 2019, 'Hybrid PD-Fuzzy and PD Controllers for Trajectory Tracking of a Quadrotor Unmanned Aerial Vehicle: Autopilot Designs and Real-Time Flight Tests', IEEE Transactions on Systems Man and Cybernetics: Systems, http://dx.doi.org/10.1109/TSMC.2019.2906320

Ferdaus MM; Pratama M; Anavatti SG; Garratt MA, 2019, 'Online identification of a rotary wing Unmanned Aerial Vehicle from data streams', Applied Soft Computing Journal, vol. 76, pp. 313 - 325, http://dx.doi.org/10.1016/j.asoc.2018.12.013

Biswas S; Anavatti SG; Garratt MA, 2019, 'Multiobjective Mission Route Planning Problem: A Neural Network-Based Forecasting Model for Mission Planning', IEEE Transactions on Intelligent Transportation Systems, http://dx.doi.org/10.1109/TITS.2019.2960057

Biswas S; Anavatti SG; Garratt MA, 2019, 'A time-efficient co-operative path planning model combined with task assignment for multi-agent systems', Robotics, vol. 8, http://dx.doi.org/10.3390/ROBOTICS8020035

Ferdaus MM; Pratama M; Anavatti S; Garratt MA; Pan Y, 2019, 'Generic Evolving Self-Organizing Neuro-Fuzzy Control of Bio-inspired Unmanned Aerial Vehicles', IEEE Transactions on Fuzzy Systems, http://dx.doi.org/10.1109/TFUZZ.2019.2917808

Debie E; Fernandez Rojas R; Fidock J; Barlow M; Kasmarik K; Anavatti S; Garratt M; Abbass H, 2019, 'Multi-Modal Fusion for Objective Assessment of Cognitive Workload: A Review', IEEE Transactions on Cybernetics

Santoso F; Garratt MA; Anavatti SG; Petersen I, 2018, 'Robust Hybrid Nonlinear Control Systems for the Dynamics of a Quadcopter Drone', IEEE Transactions on Systems, Man, and Cybernetics: Systems, http://dx.doi.org/10.1109/TSMC.2018.2836922

Francis SLX; Anavatti SG; Garratt M, 2018, 'Real-time path planning module for autonomous vehicles in cluttered environment using a 3D camera', International Journal of Vehicle Autonomous Systems, vol. 14, pp. 40 - 61, http://dx.doi.org/10.1504/IJVAS.2018.093106

Alam K; Ray T; Anavatti SG, 2017, 'Design Optimization of an Unmanned Underwater Vehicle Using Low- A nd High-Fidelity Models', IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 47, pp. 2794 - 2808, http://dx.doi.org/10.1109/TSMC.2015.2390592

Pratama M; Lughofer E; Er MJ; Anavatti S; Lim CP, 2017, 'Data driven modelling based on Recurrent Interval-Valued Metacognitive Scaffolding Fuzzy Neural Network', Neurocomputing, vol. 262, pp. 4 - 27, http://dx.doi.org/10.1016/j.neucom.2016.10.093

Za'in C; Pratama M; Lughofer E; Anavatti SG, 2017, 'Evolving type-2 web news mining', Applied Soft Computing Journal, vol. 54, pp. 200 - 220, http://dx.doi.org/10.1016/j.asoc.2016.11.034

Halder KK; Paul M; Tahtali M; Anavatti SG; Murshed M, 2017, 'Correction of geometrically distorted underwater images using shift map analysis', Journal of the Optical Society of America A: Optics and Image Science, and Vision, vol. 34, pp. 666 - 673, http://dx.doi.org/10.1364/JOSAA.34.000666

Santoso F; Anavatti SG; Garratt MA, 2017, 'State-of-the-Art Intelligent Flight Control Systems in Unmanned Aerial Vehicles', IEEE Transactions on Automation Science and Engineering, vol. 15, pp. 613 - 627, http://dx.doi.org/10.1109/TASE.2017.2651109

Pratama M; Zhang G; Er MJ; Anavatti S, 2017, 'An Incremental Type-2 Meta-Cognitive Extreme Learning Machine', IEEE Transactions on Cybernetics, vol. 47, pp. 339 - 353, http://dx.doi.org/10.1109/TCYB.2016.2514537

Wang J; Garratt MA; Anavatti SG, 2017, 'Real-time path planning algorithm for autonomous vehicles in unknown environments', International Journal of Mechatronics and Automation, vol. 6, pp. 1 - 9, http://dx.doi.org/10.1504/IJMA.2017.093238

Santoso F; Garratt MA; Anavatti SG, 2017, 'Visual-inertial navigation systems for aerial robotics: Sensor fusion and technology', IEEE Transactions on Automation Science and Engineering, vol. 14, pp. 260 - 275, http://dx.doi.org/10.1109/TASE.2016.2582752

Anavatti SG, 2017, 'Aggressive formation flying of fixedwing UAVs with Differential Geometric Guidance', Unmanned Systems, vol. 5, pp. 97 - 113, http://dx.doi.org/10.1142/S2301385017500078

Li C; Anavatti SG; Ray T, 2017, 'A Path-Based Solution Algorithm for Dynamic Traffic Assignment', Networks and Spatial Economics, vol. 17, pp. 841 - 860, http://dx.doi.org/10.1007/s11067-017-9346-1

Hassanein O; Anavatti SG; Shim H; Ray T, 2016, 'Model-based adaptive control system for autonomous underwater vehicles', Ocean Engineering, vol. 127, pp. 58 - 69, http://dx.doi.org/10.1016/j.oceaneng.2016.09.034

Tehrani MH; Garratt MA; Anavatti SG, 2016, 'Low-altitude horizon-based aircraft attitude estimation using UV-filtered panoramic images and optic flow', IEEE Transactions on Aerospace and Electronic Systems, vol. 52, pp. 2362 - 2375, http://dx.doi.org/10.1109/TAES.2016.14-0534

Pratama M; Lu J; Lughofer E; Zhang G; Anavatti S, 2016, 'Scaffolding type-2 classifier for incremental learning under concept drifts', Neurocomputing, vol. 191, pp. 304 - 329, http://dx.doi.org/10.1016/j.neucom.2016.01.049

Pratama M; Lu J; Lughofer E; Zhang G; Anavatti S, 2016, 'Scaffolding type-2 classifier for incremental learning under concept drifts', Neurocomputing, vol. 191, pp. 304 - 329, http://dx.doi.org/10.1016/j.neucom.2016.01.049

Halder KK; Tahtali M; Anavatti SG, 2016, 'Moving object detection and tracking in videos through turbulent medium', Journal of Modern Optics, vol. 63, pp. 1015 - 1021, http://dx.doi.org/10.1080/09500340.2015.1117665

Pratama M; Lu J; Anavatti S; Lughofer E; Lim CP, 2016, 'An incremental meta-cognitive-based scaffolding fuzzy neural network', Neurocomputing, vol. 171, pp. 89 - 105, http://dx.doi.org/10.1016/j.neucom.2015.06.022

Pratama M; Anavatti SG; Lu J, 2015, 'Recurrent Classifier Based on an Incremental Metacognitive-Based Scaffolding Algorithm', IEEE Transactions on Fuzzy Systems, vol. 23, pp. 2048 - 2066, http://dx.doi.org/10.1109/TFUZZ.2015.2402683

Anavatti SG; Francis S; garratt M, 2015, 'A ToF-camera as a 3D Vision Sensor for Autonomous Mobile Robotics', International Journal of Advanced Robotic Systems, vol. 12, http://dx.doi.org/10.5772/61348

Halder KK; Tahtali M; Anavatti SG, 2015, 'Geometric correction of atmospheric turbulence-degraded video containing moving objects', Optics Express, vol. 23, pp. 5091 - 5101, http://dx.doi.org/10.1364/OE.23.005091

Halder KK; Tahtali M; Anavatti SG, 2014, 'Simple algorithm for correction of geometrically warped underwater images', Electronics Letters, vol. 50, pp. 1687 - 1689, http://dx.doi.org/10.1049/el.2014.3142

Halder KK; Tahtali M; Anavatti SG, 2014, 'Model-free prediction of atmospheric warp based on artificial neural network', Applied Optics, vol. 53, pp. 7087 - 7094, http://dx.doi.org/10.1364/AO.53.007087

Halder KK; Tahtali M; Anavatti SG, 2014, 'Simple and efficient approach for restoration of non-uniformly warped images', Applied Optics, vol. 53, pp. 5576 - 5584, http://dx.doi.org/10.1364/AO.53.005576

Pratama M; Anavatti S; Er MJ; Lughofer E, 2014, 'pClass: An Effective Classifier to Streaming Examples', IEEE Transactions on Fuzzy Systems, vol. 23, pp. 1 - 1, http://dx.doi.org/10.1109/TFUZZ.2014.2312983

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