15 citations · 17 across the 5 of their papers we have counts for
5 papers
A Divide-and-Conquer Machine Learning Approach for Modelling Turbulent Flows
Anthony Man, Mohammad Jadidi, Amir Keshmiri +2
In this paper, a novel zonal machine learning (ML) approach for Reynolds-averaged Navier-Stokes (RANS) turbulence modelling based on the divide-and-conquer technique is introduced.…
Non-Unique Machine Learning Mapping in Data-Driven Reynolds Averaged Turbulence Models
Anthony Man, Mohammad Jadidi, Amir Keshmiri +2
Recent growing interest in using machine learning for turbulence modelling has led to many proposed data-driven turbulence models in the literature. However, most of these models h…
Accelerated Sim-to-Real Deep Reinforcement Learning: Learning Collision Avoidance from Human Player
Hanlin Niu, Ze Ji, Farshad Arvin +3
This paper presents a sensor-level mapless collision avoidance algorithm for use in mobile robots that map raw sensor data to linear and angular velocities and navigate in an unkno…
3D Vision-guided Pick-and-Place Using Kuka LBR iiwa Robot
Hanlin Niu, Ze Ji, Zihang Zhu +2
This paper presents the development of a control system for vision-guided pick-and-place tasks using a robot arm equipped with a 3D camera. The main steps include camera intrinsic…
Design, Integration and Sea Trials of 3D Printed Unmanned Aerial Vehicle and Unmanned Surface Vehicle for Cooperative Missions
Hanlin Niu, Ze Ji, Pietro Liguori +2
In recent years, Unmanned Surface Vehicles (USV) have been extensively deployed for maritime applications. However, USV has a limited detection range with sensor installed at the s…