Professor Ian Manchester
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Professor Ian Manchester

B. Eng (Electrical) Hons 1, PhD UNSW
Professor of Mechatronic Engineering
Director, Australian Centre for Robotics
Director, Australian Robotic Inspection &
Asset Management Hub (ARIAM)
Professor Ian Manchester

Ian Manchester received BE and PhD degrees in electrical engineering from the University of New South Wales in 2002 and 2006, respectively. From 2006-2009 he was a post-doctoral researcher at Umea University, Sweden, and from 2009-2012 he was a Research scientist at the Massachusetts Institute of Technology.

Since 2012 he has been a faculty member at the University of Sydney, Australia, where he is currently Professor of Mechatronic Engineering. In 2018 he became Director of Research for the Australian Centre for Field Robotics (ACFR), in 2019 he become co-Director of the Sydney Institute for Robotics and Intelligent Systems and was awarded a Sydney Research Accelerator Fellowship Award (SOAR).

In 2021 Professor Manchester was announced as the Director of the ACFR and led a team of academic and industry partners to found the ARC Research Hub in Intelligent Robotic Systems for Asset Management.

His current research interests are in algorithms for control, estimation, and identification of nonlinear dynamical systems. A particular focus is planning and control for challenging problems in robotics, including dynamic walking robots and multi-robot systems. He has also worked in applications in biomedical engineering, forestry, mining automation, and commercial aviation.

Prof Manchester has been an Associate Editor for IEEE Robotics and Automation Letters and has served on organising and editorial committees for many international conferences including IEEE Conference on Decision and Control, Robotics: Science and Systems, and Conference on Robot Learning.

Robotics, Nonlinear Control, System Identification, Machine Learning, Optimization

AMME5520- Advanced Control and Optimization

Robotics
Project titleResearch student
Design of Acrobatic Legged RobotsPedram AHMADIYAN ARDESTANI
Reinforcement Learning for Robotic Systems with Certified Stability and RobustnessNicholas BARBARA
Automation and robust control on Surgical RobotsJing CHENG
EPA-D: Estimation Planning and Acting in Dynamic EnvironmentsMikolaj KLINIEWSKI
Enhancing Safe Robot Control under Time-variant Dynamic Environment with LearningDechuan LIU
Improving Vision-based Control using Robust Neural NetworksRaghav MISHRA
Quadrupedal robot motion-planning and optimisationMichael SOMERFIELD
Investigating Safe Learning from Demonstration with Limited Expert SamplesBen STIRLING
Towards Long Lasting Robot Operations in Nuclear FacilitiesSharni SUJATHA
Cassie Bipedal Robot over Uneven TerrainYurui ZHANG

Publications

Journals

  • Yi, B., Manchester, I. (2024). On IMU preintegration: A nonlinear observer viewpoint and its applications. Systems and Control Letters, 193, 105933. [More Information]
  • Yi, B., Jin, C., Wang, L., Shi, G., Ila, V., Manchester, I. (2024). PEBO-SLAM: Observer Design for Visual Inertial SLAM with Convergence Guarantees. IEEE Transactions on Automatic Control. [More Information]
  • Wang, R., Tóth, R., Koelewijn, P., Manchester, I. (2024). Virtual control contraction metrics: Convex nonlinear feedback design via behavioral embedding. International Journal of Robust and Nonlinear Control. [More Information]

Conferences

  • Yi, B., Wang, L., Manchester, I. (2023). Attitude Estimation from Vector Measurements: Necessary and Sufficient Conditions and Convergent Observer Design. 12th IFAC Symposium on Nonlinear Control Systems, NOLCOS 2022, Berlin: Elsevier B.V. [More Information]
  • Wang, R., Manchester, I. (2023). Direct Parameterization of Lipschitz-Bounded Deep Networks. 40th International Conference on Machine Learning, ICML 2023, NA: ML Research Press.
  • Somers,, V., Manchester, I. (2022). Multi-Stage Sparse Resource Allocation for Control of Spreading Processes over Networks. Proceedings of the American Control Conference, : Institute of Electrical and Electronics Engineers Inc.

2024

  • Yi, B., Manchester, I. (2024). On IMU preintegration: A nonlinear observer viewpoint and its applications. Systems and Control Letters, 193, 105933. [More Information]
  • Yi, B., Jin, C., Wang, L., Shi, G., Ila, V., Manchester, I. (2024). PEBO-SLAM: Observer Design for Visual Inertial SLAM with Convergence Guarantees. IEEE Transactions on Automatic Control. [More Information]
  • Wang, R., Tóth, R., Koelewijn, P., Manchester, I. (2024). Virtual control contraction metrics: Convex nonlinear feedback design via behavioral embedding. International Journal of Robust and Nonlinear Control. [More Information]

2023

  • Yi, B., Wang, L., Manchester, I. (2023). Attitude Estimation from Vector Measurements: Necessary and Sufficient Conditions and Convergent Observer Design. 12th IFAC Symposium on Nonlinear Control Systems, NOLCOS 2022, Berlin: Elsevier B.V. [More Information]
  • Yi, B., Wang, L., Manchester, I. (2023). Attitude Estimation From Vector Measurements: Necessary and Sufficient Conditions and Convergent Observer Design. IEEE Transactions on Automatic Control. [More Information]
  • Wang, L., Manchester, I., Trumpf, J., Shi, G. (2023). Differential initial-value privacy and observability of linear dynamical systems. Automatica, 148. [More Information]

2022

  • Lee, J., Sun, Y., Sun, Y., Manchester, I., Naguib, H. (2022). Design of multi-stimuli responsive hybrid pneumatic – magnetic soft actuator with novel channel integration. Applied Materials Today, 29. [More Information]
  • Revay, M., Umenberger, J., Manchester, I. (2022). Distributed Identification of Contracting and/or Monotone Network Dynamics. IEEE Transactions on Automatic Control, 67(7), 3410-3425. [More Information]
  • Yi, B., Jin, C., Manchester, I. (2022). Globally convergent visual-feature range estimation with biased inertial measurements. Automatica, 146. [More Information]

2021

  • Revay, M., Wang, R., Manchester, I. (2021). A Convex Parameterization of Robust Recurrent Neural Networks. IEEE Control Systems Letters, 5(4), 1363-1368. [More Information]
  • Revay, M., Wang, R., Manchester, I. (2021). A Convex Parameterization of Robust Recurrent Neural Networks. 2021 American Control Conference (ACC 2021), New Orleans: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
  • Yi, B., Jing, C., Wang, L., Shi, G., Manchester, I. (2021). An almost globally convergent observer for visual SLAM without persistent excitation. 60th IEEE Conference on Decision and Control, CDC 2021, Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]

2020

  • Wang, R., Manchester, I. (2020). Continuous-time Dynamic Realization for Nonlinear Stabilization via Control Contraction Metrics. 2020 American Control Conference (ACC 2020), Denver: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
  • Kong, F., Manchester, I. (2020). Contraction analysis of nonlinear noncausal iterative learning control. Systems and Control Letters, 136, 104599. [More Information]
  • Wang, L., Manchester, I., Trumpf, J., Shi, G. (2020). Initial-Value Privacy of Linear Dynamical Systems. 59th IEEE Conference on Decision and Control, CDC 2020, Jeju Island: Institute of Electrical and Electronics Engineers (IEEE). [More Information]

2019

  • Umenberger, J., Manchester, I. (2019). Convex bounds for equation error in stable nonlinear identification. IEEE Control Systems Letters, 3(1), 73-78. [More Information]
  • Stein Shiromoto, H., Revay, M., Manchester, I. (2019). Distributed Nonlinear Control Design using Separable Control Contraction Metrics. IEEE Transactions on Control of Network Systems, 6(4), 1281-1290. [More Information]
  • Boudali, A., Sinclair, P., Manchester, I. (2019). Predicting Transitioning Walking Gaits: Hip and Knee Joint Trajectories From the Motion of Walking Canes. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 27(9), 1791-1800. [More Information]

2018

  • Manchester, I. (2018). Contracting Nonlinear Observers: Convex Optimization and Learning from Data. 2018 American Control Conference (ACC 2018), Piscaway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
  • Chaffey, T., Manchester, I. (2018). Control Contraction Metrics on Finsler Manifolds. 2018 American Control Conference (ACC 2018), Piscaway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
  • Mitchell, J., Manchester, I. (2018). Fault detection for a switched battery system via constrained nonlinear state estimation. 13th IEEE Conference on Industrial Electronics and Applications (ICIEA 2018), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]

2017

  • Kong, F., Manchester, I. (2017). Contraction Analysis of Nonlinear Iterative Learning Control. The 20th World Congress of the International Federation of Automatic Control (IFAC 2017 World Congress), online: International Federation of Automatic Control (IFAC). [More Information]
  • Manchester, I., Slotine, J. (2017). Control Contraction Metrics: Convex and Intrinsic Criteria for Nonlinear Feedback Design. IEEE Transactions on Automatic Control, 62(6), 3046-3053. [More Information]
  • Tobenkin, M., Manchester, I., Megretski, A. (2017). Convex Parameterizations and Fidelity Bounds for Nonlinear Identification and Reduced-Order Modelling. IEEE Transactions on Automatic Control, 62(7), 3679-3686. [More Information]

2016

  • Stein Shiromoto, H., Manchester, I. (2016). Decentralized nonlinear feedback design with separable control contraction metrics. 2016 IEEE 55th Conference on Decision and Control (CDC 2016), Las Vegas: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
  • Umenberger, J., Manchester, I. (2016). Scalable identification of stable positive systems. 2016 IEEE 55th Conference on Decision and Control (CDC 2016), Las Vegas: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
  • Umenberger, J., Manchester, I. (2016). Specialized algorithm for identification of stable linear systems using Lagrangian relaxation. 2016 American Control Conference (ACC 2016), Boston: Institute of Electrical and Electronics Engineers (IEEE). [More Information]

2015

  • Maeda, G., Manchester, I., Rye, D. (2015). Combined ILC and Disturbance Observer for the Rejection of Near-Repetitive Disturbances, With Application to Excavation. IEEE Transactions on Control Systems Technology, 23(5), 1754-1769. [More Information]
  • Cheong, S., Manchester, I. (2015). Input design for discrimination between classes of LTI models. Automatica, 53, 103-110. [More Information]
  • Umenberger, J., Wagberg, J., Manchester, I., Schon, T. (2015). On identification via EM with latent disturbances and lagrangian relaxation. 17th IFAC Symposium on System Identification, SYSID 2015, Beijing, China: International Federation of Automatic Control (IFAC). [More Information]

2014

  • Manchester, I., Slotine, J. (2014). Control contraction metrics and universal stabilizability. 19th World Congress The International Federation of Automatic Control, Cape Town, South Africa: International Federation of Automatic Control (IFAC). [More Information]
  • Cheong, S., Manchester, I. (2014). Input design for model discrimination and fault detection via convex relaxation. 2014 American Control Conference (ACC), Portland, Orgeon, USA: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
  • Cheong, S., Manchester, I. (2014). Model predictive control combined with model discrimination and fault detection. 19th World Congress The International Federation of Automatic Control, Cape Town, South Africa: International Federation of Automatic Control (IFAC). [More Information]

2013

  • Andersson, K., Manchester, I., Laurell, K., Cesarini, K., Malm, J., Eklund, A. (2013). Measurement of CSF dynamics with oscillating pressure infusion. Acta Neurologica Scandinavica, 128(1), 17-23. [More Information]
  • Tobenkin, M., Manchester, I., Megretski, A. (2013). Stable nonlinear identification from noisy repeated experiments via convex optimization. 1st American Control Conference (ACC 2013), Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
  • Manchester, I., Slotine, J. (2013). Transverse contraction criteria for existence, stability, and robustness of a limit cycle. 52nd IEEE Conference on Decision and Control (CDC 2013), : Institute of Electrical and Electronics Engineers Inc. [More Information]

2012

  • Manchester, I. (2012). Amplitude-constrained input design: convex relaxation and application to clinical neurology. 16th IFAC Symposium on System Identification, SYSID 2012, Brussels, Belgium: International Federation of Automatic Control (IFAC). [More Information]
  • Manchester, I., Tobenkin, M., Megretski, A. (2012). Stable Nonlinear System Identication: Convexity,Model Class, and Consistency. 16th IFAC Symposium on System Identification, SYSID 2012, Brussels, Belgium: International Federation of Automatic Control (IFAC). [More Information]

2011

  • Shkolnik, A., Levashov, M., Manchester, I., Tedrake, R. (2011). Bounding on Rough Terrain with the LittleDog Robot. International Journal of Robotics Research, 30(2), 192-215. [More Information]
  • Manchester, I., Roberts, J., Tedrake, R. (2011). Feedback Controller Parameterizations for Reinforcement Learning. IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
  • Manchester, I., Tobenkin, M., Wang, J. (2011). Identification of nonlinear systems with stable oscillations. 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC 2011), New York, USA: Institute of Electrical and Electronics Engineers (IEEE). [More Information]

2010

  • Tobenkin, M., Manchester, I., Wang, J., Megretski, A., Tedrake, R. (2010). Convex Optimization In Identification Of Stable Non-Linear State Space Models. 49th IEEE Conference on Decision and Control (CDC 2010), Atlanta: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
  • Manchester, I. (2010). Input Design for System Identification via Convex Relaxation. 49th IEEE Conference on Decision and Control (CDC 2010), Atlanta: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
  • Tedrake, R., Manchester, I., Tobenkin, M., Roberts, J. (2010). LQR-Trees: Feedback Motion Planning via Sums of Squares Verication. International Journal of Robotics Research, 29(8), 1038-1052. [More Information]

2009

  • Manchester, I. (2009). An Algorithm for Amplitude-Constrained Input Design for System Identification. Joint 48th IEEE Conference on Decision and Control and 28th Chinese Control Conference CDC/CCC 2009, Shanghai: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
  • Manchester, I., Mettin, U., Iida, F., Tedrake, R. (2009). Stable Dynamic Walking over Rough Terrain: Theory and Experiment. International Symposium on Robotics Research, Lucerne, Switzerland: Springer. [More Information]

2008

  • Manchester, I., Andersson, K., Andersson, N., Shiriaev, A., Eklund, A. (2008). A nonlinear observer for on-line estimation of the cerebrospinal fluid outflow resistance. Automatica, 44(5), 1426-1430. [More Information]
  • Shiriaev, A., Friedovich, L., Manchester, I. (2008). Can we make a robot ballerina perform a pirouette? Orbital stabilization of periodic motions of underactuated mechanical systems. Annual Reviews in Control, 32(2), 200-211. [More Information]
  • La Hera, P., Mettin, U., Manchester, I., Shiriaev, A. (2008). Identification and Control of a Hydraulic Forestry Crane. 17th International Federation of Automatic Control (IFAC) World Congress, Seoul: International Federation of Automatic Control (IFAC). [More Information]

2007

  • Low, E., Manchester, I., Savkin, A. (2007). A biologically inspired method for vision-based docking of wheeled mobile robots. Robotics and Autonomous Systems, 55(10), 769-784. [More Information]
  • Andersson, K., Manchester, I., Andersson, N., Shiriaev, A., Malm, J., Eklund, A. (2007). Assessment of cerebrospinal fluid outflow conductance using an adaptive observer—experimental and clinical evaluation. Physiological Measurement, 28(11), 1355-1368. [More Information]
  • Freidovich, L., Shiriaev, A., Manchester, I. (2007). Experimental implementation of stable oscillations of the Furuta pendulum around the upward equilibrium. IEEE/RSJ 2007 International Conference on Intelligent Robots and Systems (IROS 2007), USA: Institute of Electrical and Electronics Engineers (IEEE).

Selected Grants

2024

  • RES: ACM (formerly SoMAC) CRC HPN001 Project Agreement: Scientific and technical barriers for robotics and automation in composite manufacturing - HERA, Advanced Composite Structures, LaserBonnd, Rux Energy - Ian Manchester - RA0003167, Manchester I, Australian Composites Manufacturing CRC (ACM CRC)/Research Grant

2023

  • Harnessing the Power of Wind: Revolutionising Wind Farm Optimisation, Manchester I, Verbic G, Thornber B, Köstler H, Australian Research Council (ARC)/Discovery Projects (DP)
  • PROJECT SCHEDULE 14 (NEXXIS) ARC RESEARCH HUB IN INTELLIGENT ROBOTICS SYSTEMS FOR REAL-TIME ASSET MANAGEMENT, Manchester I, Australian Research Council (ARC)/Industrial Transformation Research Hubs (ITRH)
  • Google Philanthropic Grant: Neural Networks with Built-In Behavioural Constraints, Manchester I, Google Asia Pacific Pte. Ltd/Research Support
  • National Facility for Electricity Grid Security and Resilience Research, Shi G, Manchester I, Verbic G, Zhu J, Australian Research Council (ARC)/Linkage Infrastructure, Equipment and Facilities (LIEF)
  • Project 6: Thales AWS, ARC RESEARCH HUB IN INTELLIGENT ROBOTICS SYSTEMS FOR REAL-TIME ASSET MANAGEMENT (ARIAM), Manchester I, Australian Research Council (ARC)/Industrial Transformation Research Hubs (ITRH)
  • Project 3: Emesent (ARC ARIAM Hub), Manchester I, Australian Research Council (ARC)/Industrial Transformation Research Hubs (ITRH)