Research
Our research focuses on developing control algorithms for multi-robot topology control by utilising state-of-the-art machine learning models.
Highlighted
Pontryagin-Augmented NMPC for Stable Quadrotor Landing Under Learned Downwash Disturbances
ECC
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08 Jul 2026
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document/11625460
Neural PMP-NMPC for Adaptive and Stable Quadrotor Control in Perception-Driven Tasks
ICUAS
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16 Jun 2026
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document/11598672
Neural L1 Adaptive Control of Vehicle Lateral Dynamics
IEEE ICRA
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27 Jan 2025
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arXiv:2405.16358
System Identification and Control of Front-Steered Ackermann Vehicles Through Differentiable Physics
IEEE IROS
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13 Dec 2023
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10.1109/IROS55552.2023.10342391
Multirobot Field of View Control With Adaptive Decentralization
IEEE TR-O
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01 Feb 2022
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10.1109/TRO.2022.3142660
Distributed Adaptive and Resilient Control of Multi-Robot Systems With Limited Field of View Interactions
IEEE RA-L
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03 Mar 2021
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10.1109/LRA.2022.3155822
Hardware-in-the-loop testbed for evaluating connected vehicle applications
Transportation Research Part C Emerging Technologies
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01 May 2017
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https://doi.org/10.1016/j.trc.2017.02.01
Evaluating Connected Vehicles and Their Applications
ASME
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01 Dec 2016
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https://doi.org/10.1115/1.2016-Dec-3