High-efficient low-cost characterization of composite material properties using domain-knowledge-guided self-supervised learning
Modern AI-assisted approaches have revolutionized our abilities to better understand the
properties of concrete and composite materials. However, current machine learning models …
properties of concrete and composite materials. However, current machine learning models …
Observer-Based Multiagent Deep Reinforcement Learning: A Fully Distributed Training Scheme
L Ding, Q Mao, G Yan - IEEE Transactions on Industrial …, 2024 - ieeexplore.ieee.org
With the extensive application of multiagent reinforcement learning (MARL), it encounters
great obstacles in more complex engineering applications. Realistic environment in MARL is …
great obstacles in more complex engineering applications. Realistic environment in MARL is …
Hierarchical kernelized movement primitives for learning human-robot collaborative trajectories in referred object handover
K Qian, Z Yue, J Bai - Applied Intelligence, 2025 - Springer
While research in Learning-by-Demonstration (LbD) methods has made significant
progress, learning human-robot collaborative trajectories has been a challenging task. In …
progress, learning human-robot collaborative trajectories has been a challenging task. In …
Robot Task Primitive Segmentation from Demonstrations Using Only Built-in Kinematic State and Force-Torque Sensor Data
SLB Sørensen, TR Savarimuthu… - 2023 IEEE 19th …, 2023 - ieeexplore.ieee.org
This paper presents a method for segmentation and classification of kinesthetic
demonstrations of robot peg-in-hole tasks using a deep neural network. The presented …
demonstrations of robot peg-in-hole tasks using a deep neural network. The presented …
High-efficient low-cost characterization of materials properties using domain-knowledge-guided self-supervised learning
Modern AI-assisted approaches have helped material scientists revolutionize their abilities
to better understand the properties of materials. However, current machine learning (ML) …
to better understand the properties of materials. However, current machine learning (ML) …