1 citations · 1 across the 8 of their papers we have counts for
10 papers
Masked Generative Policy for Robotic Control
Lipeng Zhuang, Shiyu Fan, Florent P. Audonnet +4
We present Masked Generative Policy (MGP), a novel framework for visuomotor imitation learning. We represent actions as discrete tokens, and train a conditional masked transformer…
Is Task-Specific Training Necessary for Anomaly Detection?
Xingwu Zhang, Guanxuan Li, Paul Henderson +2
Current state-of-the-art multi-class unsupervised anomaly detection (MUAD) methods rely on training encoder--decoder models to reconstruct anomaly-free features. However, we argue…
3D-ADAM: A Dataset for 3D Anomaly Detection in Additive Manufacturing
Paul McHard, Florent P. Audonnet, Oliver Summerell +3
Surface defects are a primary source of yield loss in manufacturing, yet existing anomaly detection methods often fail in real-world deployment due to limited and unrepresentative…
Curio: A Cost-Effective Solution for Robotics Education
Talha Enes Ayranci, Florent P. Audonnet, Gerardo Aragon-Camarasa +2
Student engagement is one of the key challenges in robotics and artificial intelligence (AI) education. Tangible learning approaches, such as educational robots, provide an effecti…
Benchmarking machine learning models for predicting aerofoil performance
Oliver Summerell, Gerardo Aragon-Camarasa, Stephanie Ordonez Sanchez
This paper investigates the capability of Neural Networks (NNs) as alternatives to the traditional methods to analyse the performance of aerofoils used in the wind and tidal energy…
Can Real-to-Sim Approaches Capture Dynamic Fabric Behavior for Robotic Fabric Manipulation?
Yingdong Ru, Lipeng Zhuang, Zhuo He +2
This paper presents a rigorous evaluation of Real-to-Sim parameter estimation approaches for fabric manipulation in robotics. The study systematically assesses three state-of-the-a…