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Journal Articles
- 2024
[j63]Essam Soliman Debie, Kathryn Kasmarik
, Matt Garratt:
Swarm Robotics: A Survey from a Multi-Tasking Perspective. ACM Comput. Surv. 56(2): 49:1-49:38 (2024)- [j62]Praveen Kumar Muthusamy, Bhivraj Suthar, Rajkumar Muthusamy, Matthew Garratt, Hemanshu Roy Pota, Lakmal D. Seneviratne, Yahya H. Zweiri:
Self-Organizing BFBEL Control System for a UAV Under Wind Disturbance. IEEE Trans. Ind. Electron. 71(5): 5021-5033 (2024) - 2023
- [j61]Shadi Abpeikar, Kathryn Kasmarik, Matt Garratt:
Iterative transfer learning for automatic collective motion tuning on multiple robot platforms. Frontiers Neurorobotics 17 (2023) - [j60]Vu Phi Tran, Matthew A. Garratt, Kathryn Kasmarik, Sreenatha G. Anavatti:
Dynamic Frontier-Led Swarming: Multi-Robot Repeated Coverage in Dynamic Environments. IEEE CAA J. Autom. Sinica 10(3): 646-661 (2023) - [j59]Vu Phi Tran, Matthew A. Garratt, Kathryn Kasmarik, Sreenatha G. Anavatti, Alex S. Leong, Mohammad Zamani:
Multi-gas source localization and mapping by flocking robots. Inf. Fusion 91: 665-680 (2023) - [j58]Ayad Al-Mahturi, Fendy Santoso, Matthew A. Garratt, Sreenatha G. Anavatti:
A Novel Evolving Type-2 Fuzzy System for Controlling a Mobile Robot under Large Uncertainties. Robotics 12(2): 40 (2023) - [j57]Hung The Nguyen, Aya Hussein, Matthew A. Garratt, Hussein A. Abbass:
Swarm Metaverse for Multi-Level Autonomy Using Digital Twins. Sensors 23(10): 4892 (2023) - [j56]K. T. Yasas Mahima, Asanka G. Perera, Sreenatha G. Anavatti, Matt Garratt:
Exploring Adversarial Robustness of LiDAR Semantic Segmentation in Autonomous Driving. Sensors 23(23): 9579 (2023) - [j55]Vu Phi Tran, Mohamed A. Mabrok, Sreenatha G. Anavatti, Matthew A. Garratt, Ian R. Petersen:
Robust Fuzzy Q-Learning-Based Strictly Negative Imaginary Tracking Controllers for the Uncertain Quadrotor Systems. IEEE Trans. Cybern. 53(8): 5108-5120 (2023) - [j54]Vu Phi Tran, Asanka G. Perera, Matthew A. Garratt, Kathryn Kasmarik, Sreenatha G. Anavatti:
Coverage Path Planning With Budget Constraints for Multiple Unmanned Ground Vehicles. IEEE Trans. Intell. Transp. Syst. 24(11): 12506-12522 (2023) - 2022
- [j53]Ahmad Jobran Al-Mahasneh, Sreenatha G. Anavatti, Matthew A. Garratt:
Online Model-Free Reinforcement Learning for Output Feedback Tracking Control of a Class of Discrete-Time Systems With Input Saturation. IEEE Access 10: 104966-104979 (2022) - [j52]Jing Liu, Sreenatha G. Anavatti, Matthew Garratt, Kay Chen Tan, Hussein A. Abbass:
A survey, taxonomy and progress evaluation of three decades of swarm optimisation. Artif. Intell. Rev. 55(5): 3607-3725 (2022) - [j51]Deepak Rajamohan, Jonghyuk Kim, Matt Garratt, Mark Pickering:
Image based Localization under large perspective difference between Sfm and SLAM using split sim(3) optimization. Auton. Robots 46(3): 437-449 (2022) - [j50]Jing Liu, Sreenatha G. Anavatti, Matthew Garratt, Hussein A. Abbass:
Modified continuous Ant Colony Optimisation for multiple Unmanned Ground Vehicle path planning. Expert Syst. Appl. 196: 116605 (2022) - [j49]Jing Liu, Sreenatha G. Anavatti, Matthew Garratt, Hussein A. Abbass:
Multi-operator continuous ant colony optimisation for real world problems. Swarm Evol. Comput. 69: 100984 (2022) - [j48]Shadi Abpeikar, Kathryn Kasmarik, Matthew Garratt, Robert A. Hunjet, Md Mohiuddin Khan, Huanneng Qiu:
Automatic collective motion tuning using actor-critic deep reinforcement learning. Swarm Evol. Comput. 72: 101085 (2022) - [j47]Vu Phi Tran, Matthew A. Garratt, Kathryn Kasmarik, Sreenatha G. Anavatti, Shadi Abpeikar:
Frontier-led swarming: Robust multi-robot coverage of unknown environments. Swarm Evol. Comput. 75: 101171 (2022) - [j46]Praveen Kumar Muthusamy, Matthew Garratt, Hemanshu Roy Pota, Rajkumar Muthusamy:
Real-Time Adaptive Intelligent Control System for Quadcopter Unmanned Aerial Vehicles With Payload Uncertainties. IEEE Trans. Ind. Electron. 69(2): 1641-1653 (2022) - [j45]Xingshuai Dong, Matthew A. Garratt, Sreenatha G. Anavatti, Hussein A. Abbass:
Towards Real-Time Monocular Depth Estimation for Robotics: A Survey. IEEE Trans. Intell. Transp. Syst. 23(10): 16940-16961 (2022) - [j44]Xingshuai Dong, Matthew A. Garratt, Sreenatha G. Anavatti, Hussein A. Abbass:
MobileXNet: An Efficient Convolutional Neural Network for Monocular Depth Estimation. IEEE Trans. Intell. Transp. Syst. 23(11): 20134-20147 (2022) - [j43]Ayad Al-Mahturi, Fendy Santoso, Matthew A. Garratt, Sreenatha G. Anavatti:
A Robust Self-Adaptive Interval Type-2 TS Fuzzy Logic for Controlling Multi-Input-Multi-Output Nonlinear Uncertain Dynamical Systems. IEEE Trans. Syst. Man Cybern. Syst. 52(1): 655-666 (2022) - 2021
- [j42]Ayad Al-Mahturi, Fendy Santoso, Matthew A. Garratt, Sreenatha G. Anavatti:
Self-Learning in Aerial Robotics Using Type-2 Fuzzy Systems: Case Study in Hovering Quadrotor Flight Control. IEEE Access 9: 119520-119532 (2021) - [j41]Vu Phi Tran, Matthew A. Garratt, Ian R. Petersen:
Multi-vehicle formation control and obstacle avoidance using negative-imaginary systems theory. IFAC J. Syst. Control. 15: 100117 (2021) - [j40]Vu Phi Tran, Mohamed A. Mabrok, Matthew A. Garratt, Ian R. Petersen:
Hybrid adaptive negative imaginary- neural-fuzzy control with model identification for a quadrotor. IFAC J. Syst. Control. 16: 100156 (2021) - [j39]Fendy Santoso, Matthew A. Garratt, Sreenatha G. Anavatti:
State-of-the-Art Integrated Guidance and Control Systems in Unmanned Vehicles: A Review. IEEE Syst. J. 15(3): 3312-3323 (2021) - [j38]Vu Phi Tran, Fendy Santoso, Matthew A. Garratt:
Adaptive Trajectory Tracking for Quadrotor Systems in Unknown Wind Environments Using Particle Swarm Optimization-Based Strictly Negative Imaginary Controllers. IEEE Trans. Aerosp. Electron. Syst. 57(3): 1742-1752 (2021) - [j37]Essam Soliman Debie, Raul Fernandez Rojas, Justin Fidock, Michael Barlow, Kathryn Kasmarik, Sreenatha G. Anavatti, Matt Garratt, Hussein A. Abbass:
Multimodal Fusion for Objective Assessment of Cognitive Workload: A Review. IEEE Trans. Cybern. 51(3): 1542-1555 (2021) - [j36]Vu Phi Tran, Fendy Santoso, Matthew A. Garratt, Ian R. Petersen:
Fuzzy Self-Tuning of Strictly Negative-Imaginary Controllers for Trajectory Tracking of a Quadcopter Unmanned Aerial Vehicle. IEEE Trans. Ind. Electron. 68(6): 5036-5045 (2021) - [j35]Vu Phi Tran, Fendy Santoso, Matthew A. Garratt, Sreenatha G. Anavatti:
Neural Network-Based Self-Learning of an Adaptive Strictly Negative Imaginary Tracking Controller for a Quadrotor Transporting a Cable-Suspended Payload With Minimum Swing. IEEE Trans. Ind. Electron. 68(10): 10258-10268 (2021) - [j34]Vu Phi Tran, Fendy Santoso, Matthew A. Garratt, Sreenatha G. Anavatti:
Distributed Artificial Neural Networks-Based Adaptive Strictly Negative Imaginary Formation Controllers for Unmanned Aerial Vehicles in Time-Varying Environments. IEEE Trans. Ind. Informatics 17(6): 3910-3919 (2021) - [j33]Sumana Biswas, Sreenatha G. Anavatti, Matthew A. Garratt:
Multiobjective Mission Route Planning Problem: A Neural Network-Based Forecasting Model for Mission Planning. IEEE Trans. Intell. Transp. Syst. 22(1): 430-442 (2021) - [j32]Fendy Santoso, Matthew A. Garratt, Sreenatha G. Anavatti:
Hybrid PD-Fuzzy and PD Controllers for Trajectory Tracking of a Quadrotor Unmanned Aerial Vehicle: Autopilot Designs and Real-Time Flight Tests. IEEE Trans. Syst. Man Cybern. Syst. 51(3): 1817-1829 (2021) - [j31]Ahmad Jobran Al-Mahasneh, Sreenatha G. Anavatti, Matthew A. Garratt, Mahardhika Pratama:
Stable Adaptive Controller Based on Generalized Regression Neural Networks and Sliding Mode Control for a Class of Nonlinear Time-Varying Systems. IEEE Trans. Syst. Man Cybern. Syst. 51(4): 2525-2535 (2021) - [j30]Fendy Santoso, Matthew A. Garratt, Sreenatha G. Anavatti:
A Robust Hybrid of a Feedback Linearization Technique and an Interval Type-2 Fuzzy Control System for the Flapping Angle Dynamics of a Biomimetic Aircraft. IEEE Trans. Syst. Man Cybern. Syst. 51(9): 5664-5673 (2021) - 2020
- [j29]Md Meftahul Ferdaus, Sreenatha G. Anavatti, Mahardhika Pratama, Matthew A. Garratt:
Towards the use of fuzzy logic systems in rotary wing unmanned aerial vehicle: a review. Artif. Intell. Rev. 53(1): 257-290 (2020) - [j28]Md Meftahul Ferdaus, Mahardhika Pratama, Sreenatha G. Anavatti, Matthew A. Garratt, Edwin Lughofer:
PAC: A novel self-adaptive neuro-fuzzy controller for micro aerial vehicles. Inf. Sci. 512: 481-505 (2020) - [j27]Nathan K. Long, Karl Sammut, Daniel Sgarioto, Matthew Garratt, Hussein A. Abbass:
A Comprehensive Review of Shepherding as a Bio-Inspired Swarm-Robotics Guidance Approach. IEEE Trans. Emerg. Top. Comput. Intell. 4(4): 523-537 (2020) - [j26]Md Meftahul Ferdaus, Mahardhika Pratama, Sreenatha G. Anavatti, Matthew A. Garratt, Yongping Pan:
Generic Evolving Self-Organizing Neuro-Fuzzy Control of Bio-Inspired Unmanned Aerial Vehicles. IEEE Trans. Fuzzy Syst. 28(8): 1542-1556 (2020) - [j25]Fendy Santoso, Matthew A. Garratt, Sreenatha G. Anavatti:
T2-ETS-IE: A Type-2 Evolutionary Takagi-Sugeno Fuzzy Inference System With the Information Entropy-Based Pruning Technique. IEEE Trans. Fuzzy Syst. 28(10): 2665-2672 (2020) - [j24]Ahmad Jobran Al-Mahasneh, Sreenatha G. Anavatti, Matthew A. Garratt:
Self-Evolving Neural Control for a Class of Nonlinear Discrete-Time Dynamic Systems With Unknown Dynamics and Unknown Disturbances. IEEE Trans. Ind. Informatics 16(10): 6518-6529 (2020) - [j23]Fendy Santoso, Matthew A. Garratt, Sreenatha G. Anavatti, Ian R. Petersen:
Robust Hybrid Nonlinear Control Systems for the Dynamics of a Quadcopter Drone. IEEE Trans. Syst. Man Cybern. Syst. 50(8): 3059-3071 (2020) - 2019
- [j22]Md Meftahul Ferdaus, Mahardhika Pratama, Sreenatha G. Anavatti, Matthew A. Garratt:
Online identification of a rotary wing Unmanned Aerial Vehicle from data streams. Appl. Soft Comput. 76: 313-325 (2019) - [j21]Edwar Yazid, Matthew Garratt, Fendy Santoso:
Position control of a quadcopter drone using evolutionary algorithms-based self-tuning for first-order Takagi-Sugeno-Kang fuzzy logic autopilots. Appl. Soft Comput. 78: 373-392 (2019) - [j20]Md Meftahul Ferdaus, Sreenatha G. Anavatti, Matthew A. Garratt, Mahardhika Pratama:
Development of C-Means Clustering Based Adaptive Fuzzy Controller for a Flapping Wing Micro Air Vehicle. J. Artif. Intell. Soft Comput. Res. 9(2): 99-109 (2019) - [j19]Sumana Biswas, Sreenatha G. Anavatti, Matthew A. Garratt:
A Time-Efficient Co-Operative Path Planning Model Combined with Task Assignment for Multi-Agent Systems. Robotics 8(2): 35 (2019) - [j18]Md Meftahul Ferdaus, Mahardhika Pratama, Sreenatha G. Anavatti, Matthew A. Garratt:
PALM: An Incremental Construction of Hyperplanes for Data Stream Regression. IEEE Trans. Fuzzy Syst. 27(11): 2115-2129 (2019) - 2018
- [j17]Chao Wang, Andrey V. Savkin, Matthew Garratt:
A strategy for safe 3D navigation of non-holonomic robots among moving obstacles. Robotica 36(2): 275-297 (2018) - [j16]Fendy Santoso, Matthew A. Garratt, Sreenatha G. Anavatti:
State-of-the-Art Intelligent Flight Control Systems in Unmanned Aerial Vehicles. IEEE Trans Autom. Sci. Eng. 15(2): 613-627 (2018) - 2017
- [j15]Shanggang Lin, Matthew A. Garratt, Andrew J. Lambert:
Monocular vision-based real-time target recognition and tracking for autonomously landing an UAV in a cluttered shipboard environment. Auton. Robots 41(4): 881-901 (2017) - [j14]Jiefei Wang, Matthew A. Garratt, Sreenatha G. Anavatti:
Real-time path planning algorithm for autonomous vehicles in unknown environments. Int. J. Mechatronics Autom. 6(1): 1-9 (2017) - [j13]An Hung Nguyen, Thomas Guillemette, Andrew J. Lambert, Mark Pickering, Matthew A. Garratt:
Increasing feasibility of the field-programmable gate array implementation of an iterative image registration using a kernel-warping algorithm. J. Electronic Imaging 26(5): 53010 (2017) - [j12]Ping Li, Matthew A. Garratt, Andrew J. Lambert, Shanggang Lin:
Inertial-Aided Metric States and Surface Normal Estimation using a Monocular Camera. J. Intell. Robotic Syst. 87(3-4): 439-454 (2017) - [j11]Fendy Santoso, Matthew A. Garratt, Sreenatha G. Anavatti:
Visual-Inertial Navigation Systems for Aerial Robotics: Sensor Fusion and Technology. IEEE Trans Autom. Sci. Eng. 14(1): 260-275 (2017) - 2016
- [j10]Ping Li, Matthew A. Garratt, Andrew J. Lambert, Shanggang Lin:
Metric sensing and control of a quadrotor using a homography-based visual inertial fusion method. Robotics Auton. Syst. 76: 1-14 (2016) - [j9]Mohsen H. Tehrani, Matthew A. Garratt, Sreenatha G. Anavatti:
Low-altitude horizon-based aircraft attitude estimation using UV-filtered panoramic images and optic flow. IEEE Trans. Aerosp. Electron. Syst. 52(5): 2362-2375 (2016) - 2015
- [j8]Ping Li, Matthew A. Garratt, Andrew J. Lambert:
Monocular Snapshot-based Sensing and Control of Hover, Takeoff, and Landing for a Low-cost Quadrotor. J. Field Robotics 32(7): 984-1003 (2015) - 2013
- [j7]Matthew A. Garratt, Andrew J. Lambert, Hamid Teimoori:
Design of a 3D snapshot based visual flight control system using a single camera in hover. Auton. Robots 34(1-2): 19-34 (2013) - 2012
- [j6]Matthew A. Garratt, Sreenatha G. Anavatti:
Non-linear Control of Heave for an Unmanned Helicopter Using a Neural Network. J. Intell. Robotic Syst. 66(4): 495-504 (2012) - [j5]Michael Hoy, Alexey S. Matveev, Matt Garratt, Andrey V. Savkin:
Collision-free navigation of an autonomous unmanned helicopter in unknown urban environments: sliding mode and MPC approaches. Robotica 30(4): 537-550 (2012) - 2011
- [j4]Xilin Yang, Matthew Garratt, Hemanshu Roy Pota:
Monotonous Trend Estimation of Deck Displacement for Automatic Landing of Rotorcraft UAVs. J. Intell. Robotic Syst. 61(1-4): 267-285 (2011) - [j3]Xilin Yang, Matthew Garratt, Hemanshu Roy Pota:
Flight validation of a feedforward gust-attenuation controller for an autonomous helicopter. Robotics Auton. Syst. 59(12): 1070-1079 (2011) - 2008
- [j2]Matthew A. Garratt, Javaan S. Chahl:
Vision-based terrain following for an unmanned rotorcraft. J. Field Robotics 25(4-5): 284-301 (2008) - 2006
- [j1]So-Ryeok Oh, Kaustubh Pathak, Sunil Kumar Agrawal, Hemanshu Roy Pota, Matthew Garratt:
Approaches for a tether-guided landing of an autonomous helicopter. IEEE Trans. Robotics 22(3): 536-544 (2006)
Conference and Workshop Papers
- 2023
- [c72]Md Mohiuddin Khan, Kathryn Kasmarik, Michael Barlow, Shadi Abpeikar, Huanneng Qiu, Essam Soliman Debie, Matt Garratt:
Generating Collective Motion Behaviour Libraries Using Developmental Evolution. AI (2) 2023: 441-452 - [c71]Noha Khattab, Shadi Abpeikar, Kathryn Kasmarik, Matthew Garratt:
Autonomous Recognition of Collective Motion Behaviours in Robotic Swarms from Video using a Deep Neural Network. IJCNN 2023: 1-8 - [c70]Michelle Rossouw, Sridhar Ravi, Matt Garratt:
Bio-Inspired blimps and multiple-agent source localisation. ROBIO 2023: 1-6 - 2022
- [c69]Md Mohiuddin Khan, Kathryn Kasmarik, Matt Garratt:
Decentralizing Self-organizing Maps. AI 2022: 480-493 - [c68]Shadi Abpeikar, Kathryn Kasmarik, Phi Vu Tran, Matt Garratt:
Transfer Learning for Autonomous Recognition of Swarm Behaviour in UGVs. AI 2022: 531-542 - [c67]Shadi Abpeikar, Kathryn Kasmarik, Matt Garratt:
Reinforcement Learning for Collective Motion Tuning in the Presence of Extrinsic Goals. AI 2022: 761-774 - [c66]Xingshuai Dong, Matthew A. Garratt, Sreenatha G. Anavatti, Hussein A. Abbass, Junyu Dong:
Lightweight Monocular Depth Estimation with an Edge Guided Network. ICARCV 2022: 204-210 - 2021
- [c65]Jing Liu, Aya Hussein, Sreenatha G. Anavatti, Matthew Garratt, Hussein A. Abbass:
UGV Path Planning based on an Improved Continuous Ant Colony Optimisation Algorithm. SSCI 2021: 1-8 - 2020
- [c64]Kathryn Kasmarik, Shadi Abpeikar, Md Mohiuddin Khan, Noha Khattab, Michael Barlow, Matt Garratt:
Autonomous Recognition of Collective Behaviour in Robot Swarms. Australasian Conference on Artificial Intelligence 2020: 281-293 - [c63]Deepak Rajamohan, Matthew Garratt, Mark Pickering:
A 3D-2D Registration Method for Stereo Scan Overlay on Structure from Motion Model. DICTA 2020: 1-7 - [c62]Ayad Al-Mahturi, Fendy Santoso, Matthew A. Garratt, Sreenatha G. Anavatti:
A Simplified Model-Free Self-Evolving TS Fuzzy Controller for Nonlinear Systems with Uncertainties. EAIS 2020: 1-6 - [c61]Huanneng Qiu, Matthew Garratt, David Howard, Sreenatha G. Anavatti:
Towards crossing the reality gap with evolved plastic neurocontrollers. GECCO 2020: 130-138 - [c60]Keeley A. Crockett, Matthew A. Garratt, Annabel Latham, Edwin Colyer, Sean Goltz:
Risk and Trust Perceptions of the Public of Artifical Intelligence Applications. IJCNN 2020: 1-8 - [c59]Tung Nguyen, Jing Liu, Hung The Nguyen, Kathryn Kasmarik, Sreenatha G. Anavatti, Matthew Garratt, Hussein A. Abbass:
Perceptron-Learning for Scalable and Transparent Dynamic Formation in Swarm-on-Swarm Shepherding. IJCNN 2020: 1-8 - [c58]Ayad Al-Mahturi, Fendy Santoso, Matthew A. Garratt, Sreenatha G. Anavatti:
Online System Identification for Nonlinear Uncertain Dynamical Systems Using Recursive Interval Type-2 TS Fuzzy C-means Clustering. SSCI 2020: 1695-1701 - [c57]Huanneng Qiu, Matthew Garratt, David Howard, Sreenatha G. Anavatti:
Evolving Spiking Neurocontrollers for UAVs. SSCI 2020: 1928-1935 - [c56]Hung The Nguyen, Matthew Garratt, Lam Thu Bui, Hussein A. Abbass:
Disturbances in Influence of a Shepherding Agent is More Impactful than Sensorial Noise During Swarm Guidance. SSCI 2020: 2257-2264 - 2019
- [c55]Keeley A. Crockett, Sean Goltz, Matt Garratt, Annabel Latham:
Trust in Computational Intelligence Systems: A Case Study in Public Perceptions. CEC 2019: 3227-3234 - [c54]Ayad Al-Mahturi, Fendy Santoso, Matthew A. Garratt, Sreenatha G. Anavatti:
An Intelligent Control of an Inverted Pendulum Based on an Adaptive Interval Type-2 Fuzzy Inference System. FUZZ-IEEE 2019: 1-6 - [c53]Raul Fernandez Rojas, Essam Soliman Debie, Justin Fidock, Michael Barlow, Kathryn Kasmarik, Sreenatha G. Anavatti, Matthew Garratt, Hussein A. Abbass:
Encephalographic Assessment of Situation Awareness in Teleoperation of Human-Swarm Teaming. ICONIP (4) 2019: 530-539 - [c52]Hung The Nguyen, Tung D. Nguyen, Matthew Garratt, Kathryn Kasmarik, Sreenatha G. Anavatti, Michael Barlow, Hussein A. Abbass:
A Deep Hierarchical Reinforcement Learner for Aerial Shepherding of Ground Swarms. ICONIP (1) 2019: 658-669 - [c51]Hung The Nguyen, Matthew Garratt, Lam Thu Bui, Hussein A. Abbass:
Apprenticeship Learning for Continuous State Spaces and Actions in a Swarm-Guidance Shepherding Task. SSCI 2019: 102-109 - [c50]Md Meftahul Ferdaus, Sreenatha G. Anavatti, Matthew A. Garratt, Mahardhika Pratama:
Red-FLC: an Adaptive Fuzzy Logic Controller with Reduced Learning Parameters. SSCI 2019: 513-518 - [c49]Ayad Al-Mahturi, Fendy Santoso, Matthew A. Garratt, Sreenatha G. Anavatti, Md Meftahul Ferdaus:
Online Takagi-Sugeno Fuzzy Identification of a Quadcopter Using Experimental Input-Output Data. SSCI 2019: 527-533 - [c48]Ahmad Jobran Al-Mahasneh, Sreenatha G. Anavatti, Matthew A. Garratt:
Evolving General Regression Neural Networks for Learning from Noisy Datasets. SSCI 2019: 1473-1478 - [c47]Jing Liu, Sreenatha G. Anavatti, Matthew Garratt, Hussein A. Abbass:
Comprehensive Learning Particle Swarm Optimisation with Limited Local Search for UAV Path Planning. SSCI 2019: 2287-2294 - 2018
- [c46]Hung The Nguyen, Matthew Garratt, Lam Thu Bui, Hussein A. Abbass:
Apprenticeship Bootstrapping: Inverse Reinforcement Learning in a Multi-Skill UAV-UGV Coordination Task. AAMAS 2018: 2204-2206 - [c45]Deepak Rajamohan, Mark Pickering, Matthew Garratt:
Using Edge Position Difference and Pixel Correlation for Aligning Stereo-Camera Generated 3D Scans. DICTA 2018: 1-5 - [c44]Fendy Santoso, Matthew A. Garratt, Sreenatha G. Anavatti, Osama Hassanein:
Entropy Fuzzy System Identification for the Dynamics of the Dragonfly-like Flapping Wing Aircraft. FUZZ-IEEE 2018: 1-8 - [c43]Keeley A. Crockett, Sean Goltz, Matt Garratt:
GDPR Impact on Computational Intelligence Research. IJCNN 2018: 1-7 - [c42]Hung The Nguyen, Matthew Garratt, Hussein A. Abbass:
Apprenticeship Bootstrapping. IJCNN 2018: 1-8 - [c41]Tung Nguyen, Hung The Nguyen, Essam Soliman Debie, Kathryn Kasmarik, Matthew Garratt, Hussein A. Abbass:
Swarm Q-Leaming With Knowledge Sharing Within Environments for Formation Control. IJCNN 2018: 1-8 - [c40]Md Meftahul Ferdaus, Mahardhika Pratama, Sreenatha G. Anavatti, Matthew Garratt:
A Generic Self-Evolving Neuro-Fuzzy Controller Based High-Performance Hexacopter Altitude Control System. SMC 2018: 2784-2791 - [c39]Praveen Kumar Muthusamy, Matthew Garratt, Hemanshu Roy Pota, Jiefei Wang, Jia Ming Kok:
Bidirectional Fuzzy Brain Emotional Learning Control for Aerial Robots. SSCI 2018: 146-153 - [c38]Ayad Al-Mahturi, Fendy Santoso, Matthew A. Garratt, Sreenatha G. Anavatti:
Nonlinear Altitude Control of a Quadcopter Drone Using Interval Type-2 Fuzzy Logic. SSCI 2018: 236-241 - [c37]Ahmad Jobran Al-Mahasneh, Sreenatha G. Anavatti, Matthew A. Garratt, Mahardhika Pratama:
Evolving General Regression Neural Networks using Limited Incremental Evolution for Data-Driven Modeling of Non-linear Dynamic Systems. SSCI 2018: 335-341 - [c36]Huanneng Qiu, Matthew Garratt, David Howard, Sreenatha G. Anavatti:
Evolving Spiking Neural Networks for Nonlinear Control Problems. SSCI 2018: 1367-1373 - [c35]Md Meftahul Ferdaus, Sreenatha G. Anavatti, Mahardhika Pratama, Matthew A. Garratt:
A Novel Self-Organizing Neuro-Fuzzy based Intelligent Control System for a AR.Drone Quadcopter. SSCI 2018: 2026-2032 - 2017
- [c34]Vu Phi Tran, Matthew Garratt, Ian R. Petersen:
Formation control of multi-UAVs using negative-imaginary systems theory. ASCC 2017: 2031-2036 - [c33]Ahmad Jobran Al-Mahasneh, S. G. Anavatu, Matthew A. Garratt:
Nonlinear multi-input multi-output system identification using neuro-evolutionary methods for a quadcopter. ICACI 2017: 217-222 - [c32]Md Meftahul Ferdaus, Sreenatha G. Anavatti, Matthew A. Garratt, Mahardhika Pratama:
Fuzzy clustering based nonlinear system identification and controller development of Pixhawk based quadcopter. ICACI 2017: 223-230 - [c31]Ahmad Jobran Al-Mahasneh, Sreenatha G. Anavatti, Matthew A. Garratt:
Altitude identification and intelligent control of a flapping wing micro aerial vehicle using modified generalized regression neural networks. SSCI 2017: 1-6 - [c30]Sumana Biswas, Sreenatha G. Anavatti, Matthew A. Garratt:
Particle swarm optimization based co-operative task assignment and path planning for multi-agent system. SSCI 2017: 1-6 - [c29]Md Meftahul Ferdaus, Sreenatha G. Anavatti, Matthew A. Garratt, Mahardhika Pratama:
Fuzzy clustering based modelling and adaptive controlling of a flapping wing micro air vehicle. SSCI 2017: 1-6 - [c28]Md Meftahul Ferdaus, Mahardhika Pratama, Sreenatha G. Anavatti, Matthew A. Garratt:
Evolving neuro-fuzzy system based online identification of a bio-inspired flapping wing micro aerial vehicle. SSCI 2017: 1-8 - [c27]Hung The Nguyen, Matthew Garratt, Lam Thu Bui, Hussein A. Abbass:
Supervised deep actor network for imitation learning in a ground-air UAV-UGVs coordination task. SSCI 2017: 1-8 - 2016
- [c26]Sumana Biswas, Sreenatha G. Anavatti, Matthew A. Garratt, Mahardhika Pratama:
Simultaneous replanning with vectorized particle swarm optimization algorithm. ICARCV 2016: 1-6 - [c25]Sumana Biswas, Sreenatha G. Anavatti, Matthew A. Garratt:
Proceedings in Adaptation, Learning and Optimization. IES 2016: 61-74 - 2015
- [c24]Jiefei Wang, Matthew A. Garratt, Sreenatha G. Anavatti:
Dominant plane detection using a RGB-D camera for autonomous navigation. ICARA 2015: 456-460 - [c23]Ping Li, Matthew A. Garratt, Andrew J. Lambert:
A monocular odometer for a quadrotor using a homography model and inertial cues. ROBIO 2015: 570-575 - [c22]Jiefei Wang, Matthew A. Garratt, Sreenatha G. Anavatti, Shanggang Lin:
Real-time visual odometry for autonomous MAV navigation using RGB-D camera. ROBIO 2015: 1353-1358 - [c21]Ping Li, Matthew A. Garratt, Andrew J. Lambert:
Inertial-aided state and slope estimation using a monocular camera. ROBIO 2015: 2431-2435 - 2014
- [c20]Jiefei Wang, Matthew A. Garratt, Ping Li, Sreenatha G. Anavatti:
Motion recovery using the image interpolation algorithm and an RGB-D camera. ROBIO 2014: 683-688 - 2013
- [c19]Mahardhika Pratama, Sreenatha G. Anavatti, Matthew A. Garratt, Edwin Lughofer:
Online identification of complex multi-input-multi-output system based on generic evolving neuro-fuzzy inference system. EAIS 2013: 106-113 - [c18]Sobers L. X. Francis, Sreenatha G. Anavatti, Matthew A. Garratt:
Real time cooperative path planning for multi-autonomous vehicles. ICACCI 2013: 1053-1057 - 2012
- [c17]Hamid Teimoori, Hemanshu Roy Pota, Matthew A. Garratt, Mahendra Kumar Samal:
Helicopter flight control using inverse optimal control and backstepping. ICARCV 2012: 978-983 - [c16]Sobers L. X. Francis, Sreenatha G. Anavatti, Matthew A. Garratt:
Motion Detection and Velocity Estimation for Obstacle Avoidance using 3D Point Clouds. ICINCO (2) 2012: 255-259 - [c15]Mahendra Kumar Samal, Sreenatha G. Anavatti, Matthew A. Garratt:
Neural Network Based Model Predictive Controller for Simplified Heave Model of an Unmanned Helicopter. SEMCCO 2012: 356-363 - 2011
- [c14]Xilin Yang, Matt Garratt, Hemanshu Roy Pota:
Monotonous trend estimation using recursive Prony Analysis. AuCC 2011: 321-326 - [c13]Sobers L. X. Francis, Sreenatha G. Anavatti, Matthew A. Garratt:
Reconstructing the geometry of an object using 3D TOF Camera. CompSens 2011: 13-17 - [c12]Sobers L. X. Francis, Sreenatha G. Anavatti, Matthew A. Garratt:
Dynamic model of autonomous ground vehicle for the path planning module. ICARA 2011: 73-77 - [c11]Sobers L. X. Francis, Sreenatha G. Anavatti, Matthew A. Garratt:
Model Based Path Planning Module. ICARA (selected extended papers) 2011: 81-90 - 2010
- [c10]Michael Hoy, Andrey V. Savkin, Matt Garratt:
Navigation of an unmanned helicopter in urban environments. ICARCV 2010: 939-944 - 2009
- [c9]Xilin Yang, Hemanshu Roy Pota, Matthew Garratt:
Design of a gust-attenuation controller for landing operations of Unmanned Autonomous Helicopters. CCA/ISIC 2009: 1300-1305 - 2008
- [c8]Bilal Ahmed, Hemanshu Roy Pota, Matthew Garratt:
Flight control of a rotary wing UAV - a practical approach. CDC 2008: 5042-5047 - [c7]Xilin Yang, Hemanshu Roy Pota, Matthew Garratt, Valery A. Ugrinovskii:
Prediction of vertical motions for landing operations of UAVs. CDC 2008: 5048-5053 - [c6]Abhijit G. Kallapur, Mahendra Kumar Samal, Vishwas R. Puttige, Sreenatha G. Anavatti, Matthew Garratt:
A UKF-NN Framework for System Identification of Small Unmanned Aerial Vehicles. ITSC 2008: 1021-1026 - 2007
- [c5]Bilal Ahmed, Hemanshu Roy Pota, Matthew Garratt:
Rotary wing UAV position control using backstepping. CDC 2007: 1957-1962 - 2006
- [c4]Hemanshu Roy Pota, Bilal Ahmed, Matt Garratt:
Velocity Control of a UAV using Backstepping Control. CDC 2006: 5894-5899 - [c3]Matt Garratt, Bilal Ahmed, Hemanshu Roy Pota:
Platform Enhancements and System Identification for Control of an Unmanned Helicopter. ICARCV 2006: 1-6 - 2005
- [c2]So-Ryeok Oh, Kaustubh Pathak, Sunil Kumar Agrawal, Hemanshu Roy Pota, Matt Garratt:
Autonomous Helicopter Landing on a Moving Platform Using a Tether. ICRA 2005: 3960-3965 - 2001
- [c1]Mandyam V. Srinivasan, Shao-Wu Zhang, Javaan S. Chahl, Matthew A. Garratt:
Landing Strategies in Honeybees, and Applications to UAVs. ISRR 2001: 373-384
Informal and Other Publications
- 2023
- [i23]Vu Phi Tran, Asanka G. Perera, Matthew A. Garratt, Kathryn Kasmarik, Sreenatha G. Anavatti:
Coverage Path Planning with Budget Constraints for Multiple Unmanned Ground Vehicles. CoRR abs/2306.04083 (2023) - [i22]Harriet Farlow, Matthew Garratt, Gavin Mount, Tim Lynar:
The race to robustness: exploiting fragile models for urban camouflage and the imperative for machine learning security. CoRR abs/2306.14609 (2023) - [i21]Asanka G. Perera, Vu Phi Tran, Sreenatha G. Anavatti, Kathryn Kasmarik, Matthew Garratt:
Radio Source Localization using Sparse Signal Measurements from Uncrewed Ground Vehicles. CoRR abs/2312.03493 (2023) - 2022
- [i20]Vu Phi Tran, Mohamed A. Mabrok, Sreenatha G. Anavatti, Matthew A. Garratt, Ian R. Petersen:
Robust Fuzzy Q-Learning-Based Strictly Negative Imaginary Tracking Controllers for the Uncertain Quadrotor Systems. CoRR abs/2203.13959 (2022) - [i19]Nathan K. Long, Daniel Sgarioto, Matthew Garratt, Karl Sammut:
Response Component Analysis for Sea State Estimation Using Artificial Neural Networks and Vessel Response Spectral Data. CoRR abs/2205.02375 (2022) - [i18]Xingshuai Dong, Matthew A. Garratt, Sreenatha G. Anavatti, Hussein A. Abbass, Junyu Dong:
Lightweight Monocular Depth Estimation with an Edge Guided Network. CoRR abs/2209.14829 (2022) - 2021
- [i17]Xingshuai Dong, Matthew A. Garratt, Sreenatha G. Anavatti, Hussein A. Abbass:
Towards Real-Time Monocular Depth Estimation for Robotics: A Survey. CoRR abs/2111.08600 (2021) - [i16]Xingshuai Dong, Matthew A. Garratt, Sreenatha G. Anavatti, Hussein A. Abbass:
MobileXNet: An Efficient Convolutional Neural Network for Monocular Depth Estimation. CoRR abs/2111.12334 (2021) - [i15]Vu Phi Tran, Matthew A. Garratt, Kathryn Kasmarik, Sreenatha G. Anavatti:
Robust Multi-Robot Coverage of Unknown Environments using a Distributed Robot Swarm. CoRR abs/2111.14295 (2021) - 2020
- [i14]Huanneng Qiu, Matthew Garratt, David Howard, Sreenatha G. Anavatti:
Crossing the Reality Gap with Evolved Plastic Neurocontrollers. CoRR abs/2002.09854 (2020) - [i13]Hung The Nguyen, Tung Nguyen, Vu Phi Tran, Matthew Garratt, Kathryn Kasmarik, Sreenatha G. Anavatti, Michael Barlow, Hussein A. Abbass:
Continuous Deep Hierarchical Reinforcement Learning for Ground-Air Swarm Shepherding. CoRR abs/2004.11543 (2020) - [i12]Hung The Nguyen, Matthew Garratt, Lam Thu Bui, Hussein A. Abbass:
Disturbances in Influence of a Shepherding Agent is More Impactful than Sensorial Noise During Swarm Guidance. CoRR abs/2008.12708 (2020) - 2019
- [i11]Huanneng Qiu, Matthew Garratt, David Howard, Sreenatha G. Anavatti:
Evolving Spiking Neural Networks for Nonlinear Control Problems. CoRR abs/1903.01180 (2019) - [i10]Nathan K. Long, Karl Sammut, Daniel Sgarioto, Matthew Garratt, Hussein A. Abbass:
A Comprehensive Review of Shepherding as a Bio-inspired Swarm-Robotics Guidance Approach. CoRR abs/1912.07796 (2019) - 2018
- [i9]Md Meftahul Ferdaus, Mahardhika Pratama, Sreenatha G. Anavatti, Matthew A. Garratt, Yongping Pan:
Generic Evolving Self-Organizing Neuro-Fuzzy Control of Bio-inspired Unmanned Aerial Vehicles. CoRR abs/1802.00635 (2018) - [i8]Md Meftahul Ferdaus, Sreenatha G. Anavatti, Matthew A. Garratt, Mahardhika Pratama:
Development of c-means Clustering Based Adaptive Fuzzy Controller for A Flapping Wing Micro Air Vehicle. CoRR abs/1802.01262 (2018) - [i7]Md Meftahul Ferdaus, Mahardhika Pratama, Sreenatha G. Anavatti, Matthew A. Garratt:
A Generic Self-Evolving Neuro-Fuzzy Controller based High-performance Hexacopter Altitude Control System. CoRR abs/1805.02508 (2018) - [i6]Mahardhika Pratama, Md Meftahul Ferdaus, Sreenatha G. Anavatti, Matthew A. Garratt:
PALM: An Incremental Construction of Hyperplanes for Data Stream Regression. CoRR abs/1805.04258 (2018) - [i5]Ahmad Jobran Al-Mahasneh, Sreenatha G. Anavatti, Matthew A. Garratt:
Review of Applications of Generalized Regression Neural Networks in Identification and Control of Dynamic Systems. CoRR abs/1805.11236 (2018) - [i4]Hung The Nguyen, Vu Phi Tran, Tung Nguyen, Matthew Garratt, Kathryn Kasmarik, Michael Barlow, Sreenatha G. Anavatti, Hussein A. Abbass:
Apprenticeship Bootstrapping Via Deep Learning with a Safety Net for UAV-UGV Interaction. CoRR abs/1810.04344 (2018) - [i3]Md Meftahul Ferdaus, Mahardhika Pratama, Sreenatha G. Anavatti, Matthew A. Garratt, Edwin Lughofer:
PAC: A Novel Self-Adaptive Neuro-Fuzzy Controller for Micro Aerial Vehicles. CoRR abs/1811.03764 (2018) - [i2]Vu Phi Tran, Matthew Garratt, Ian R. Petersen:
Distributed Obstacle and Multi-Robot Collision Avoidance in Uncertain Environments. CoRR abs/1811.06196 (2018) - [i1]Vu Phi Tran, Matthew Garratt, Ian R. Petersen:
Time-Varying Formation Control of a Collaborative Multi-Agent System Using Negative-Imaginary Systems Theory. CoRR abs/1811.06206 (2018)
Coauthor Index
[j60] [j59] [j58] [j56] [j55] [j54] [j53] [j52] [j50] [j49] [j47] [j45] [j44] [j43] [j42] [j39] [j37] [j35] [j34] [j33] [j32] [j31] [j30] [j29] [j28] [j26] [j25] [j24] [j23] [j22] [j20] [j19] [j18] [j16] [j14] [j11] [j9] [j6] [c66] [c65] [c62] [c61] [c59] [c58] [c57] [c54] [c53] [c52] [c50] [c49] [c48] [c47] [c44] [c40] [c38] [c37] [c36] [c35] [c32] [c31] [c30] [c29] [c28] [c26] [c25] [c24] [c22] [c20] [c19] [c18] [c16] [c15] [c13] [c12] [c11] [c6] [i23] [i21] [i20] [i18] [i17] [i16] [i15] [i14] [i13] [i11] [i9] [i8] [i7] [i6] [i5] [i4] [i3]
Phi Vu Tran
aka: Vu Phi Tran
aka: Vu Phi Tran
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