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20212025
most citedA Fully-autonomous Framework of Unmanned Surface Vehicles in Maritime Environments using Gaussian Process Motion Planning

27 citations · 34 across the 6 of their papers we have counts for

collaborators

6 papers

cs.RO2025

Active Tracking of Marine Pollution Sources: An Uncertainty-Aware Categorical Bayesian Framework for Unmanned Surface Vehicles

Song Ma, Yanchao Wang, Yewei Huang +2

This paper presents an uncertainty-aware framework for the active tracking of marine pollution sources using Unmanned Surface Vehicles (USVs). The proposed framework employs an Inf…

cs.RO2024

Dynamic Obstacle Avoidance of Unmanned Surface Vehicles in Maritime Environments Using Gaussian Processes Based Motion Planning

Jiawei Meng, Yuanchang Liu, Danail Stoyanov

During recent years, unmanned surface vehicles are extensively utilised in a variety of maritime applications such as the exploration of unknown areas, autonomous transportation, o…

math.OC2023★ 4 cited

A novel model-based parameters estimation combining local optimization and global optimization of nonlinear ship models with physical experiment dataset

Xu You, Xinping Yan, Jialun Liu +2

Designing an autonomous precise controller for ships requires accurate and reliable ship models, including the ship dynamic model and actuator model. However, selecting a suitable…

cs.RO2023★ 1 cited

Local Path Planning among Pushable Objects based on Reinforcement Learning

Linghong Yao, Valerio Modugno, Andromachi Maria Delfaki +3

In this paper, we introduce a method to deal with the problem of robot local path planning among pushable objects -- an open problem in robotics. In particular, we achieve that by…

cs.RO2022★ 27 cited

A Fully-autonomous Framework of Unmanned Surface Vehicles in Maritime Environments using Gaussian Process Motion Planning

Jiawei Meng, Ankita Humne, Richard Bucknall +2

Unmanned surface vehicles (USVs) are of increasing importance to a growing number of sectors in the maritime industry, including offshore exploration, marine transportation and def…

eess.SY2021★ 2 cited

An Intelligent Energy Management Framework for Hybrid-Electric Propulsion Systems Using Deep Reinforcement Learning

Peng Wu, Julius Partridge, Enrico Anderlini +2

Hybrid-electric propulsion systems powered by clean energy derived from renewable sources offer a promising approach to decarbonise the world's transportation systems. Effective en…