no code implementations • 2 Jun 2024 • Kabirat Olayemi, Mien Van, Luke Maguire, Sean McLoone
Reinforcement Learning (RL) or Deep Reinforcement Learning (DRL) is a powerful approach to solving Markov Decision Processes (MDPs) when the model of the environment is not known a priori.
no code implementations • 23 Mar 2024 • Nhat Minh Nguyen, Stephen McIlvanna, Jack Close, Mien Van
In this work, we propose a novel control scheme for creating multi-agent distributed formation control with limited communication between individual agents.
no code implementations • 27 Feb 2023 • Mien Van, Yuzhu Sun, Stephen Mcllvanna, Minh-Nhat Nguyen, Federico Zocco, Zhijie Liu, Hsueh-Cheng Wang
This study proposes a new distributed control method based on an adaptive fuzzy control for multiple collaborative autonomous underwater vehicles (AUVs) to track a desired formation shape within a fixed time.
no code implementations • 16 Jan 2023 • Federico Zocco, Hsueh-Cheng Wang, Mien Van
While the concept of a digital twin to support maritime operations is gaining attention for predictive maintenance, real-time monitoring, control, and overall process optimization, clarity on its implementation is missing in the literature.
no code implementations • 21 Nov 2022 • Nhat Nguyen Minh, Stephen McIlvanna, Yuzhu Sun, Yan Jin, Mien Van
We formulate the control synthesis problem as an optimal control problem that enforces control barrier function (CBF) constraints to achieve obstacle avoidance.
1 code implementation • 14 Mar 2022 • Federico Zocco, Ching-I Huang, Hsueh-Cheng Wang, Mohammad Omar Khyam, Mien Van
Subsequently, we created and made publicly available a dataset for the detection of in-water plastic bags and bottles and trained our improved EfficientDets on this and another dataset for marine debris detection.
no code implementations • 3 Aug 2021 • Dianhao Zhang, Ngo Anh Vien, Mien Van, Sean McLoone
3D skeleton-based motion prediction and activity recognition are two interwoven tasks in human behaviour analysis.