Imitation learning for sim-to-real adaptation of robotic cutting policies based on residual Gaussian process disturbance force model

J Hathaway, R Stolkin… - 2024 IEEE/RSJ …, 2024 - ieeexplore.ieee.org
Robotic cutting, a crucial task in applications such as disassembly and decommissioning,
faces challenges due to uncertainties in real-world environments. This paper presents a …

Imitation learning for sim-to-real transfer of robotic cutting policies based on residual Gaussian process disturbance force model

J Hathaway, R Stolkin, A Rastegarpanah - arXiv preprint arXiv:2311.04096, 2023 - arxiv.org
Robotic cutting, or milling, plays a significant role in applications such as disassembly,
decommissioning, and demolition. Planning and control of cutting in real-world scenarios in …

Multi-dimensional Gaussian Process-based Control for Compensation of Multi-state Dependent Disturbance

H Yeo, H Jung, S Oh - 2024 IEEE International Conference on …, 2024 - ieeexplore.ieee.org
High-precision linear motor stages have been widely used for their excellent positioning
accuracy and speed. However, core-type linear motor stages have performance limitations …

Estimation of Multi-state Dependent Disturbance by Using Multi-dimensional Gaussian Process

H Yeo, H Jung, S Oh - 2024 IEEE 33rd International …, 2024 - ieeexplore.ieee.org
High-precision linear motor stages have been widely used for their excellent positioning
accuracy and speed. However, core-type linear motor stages have performance limitations …

Nonlinear Autoregressive with Gaussian Process Regression-Based Path-Following Guidance for UAV Under Time-Varying Disturbances

D Yoon, YW Kim, B Kim, CH Lee - International Conference on Robot …, 2022 - Springer
This paper investigates the problem of the degradation of trajectory tracking performance for
an unmanned aerial vehicle under unknown external disturbances such as wind. We …