Survey of imitation learning for robotic manipulation

B Fang, S Jia, D Guo, M Xu, S Wen, F Sun - International Journal of …, 2019 - Springer
With the development of robotics, the application of robots has gradually evolved from
industrial scenes to more intelligent service scenarios. For multitasking operations of robots …

Dark, beyond deep: A paradigm shift to cognitive ai with humanlike common sense

Y Zhu, T Gao, L Fan, S Huang, M Edmonds, H Liu… - Engineering, 2020 - Elsevier
Recent progress in deep learning is essentially based on a “big data for small tasks”
paradigm, under which massive amounts of data are used to train a classifier for a single …

L F-TOUCH: A Wireless GelSight With Decoupled Tactile and Three-Axis Force Sensing

W Li, M Wang, J Li, Y Su, DK Jha, X Qian… - IEEE Robotics and …, 2023 - ieeexplore.ieee.org
GelSight sensors that estimate contact geometry and force by reconstructing the deformation
of their soft elastomer from images would yield poor force measurements when the …

A massively parallel and scalable multi-GPU material point method

X Wang, Y Qiu, SR Slattery, Y Fang, M Li… - ACM Transactions on …, 2020 - dl.acm.org
Harnessing the power of modern multi-GPU architectures, we present a massively parallel
simulation system based on the Material Point Method (MPM) for simulating physical …

Scene reconstruction with functional objects for robot autonomy

M Han, Z Zhang, Z Jiao, X ** and cad model alignments
M Han, Z Zhang, Z Jiao, X **e, Y Zhu… - … on Robotics and …, 2021 - ieeexplore.ieee.org
In this paper, we rethink the problem of scene reconstruction from an embodied agent's
perspective: While the classic view focuses on the reconstruction accuracy, our new …

On the learning mechanisms in physical reasoning

S Li, K Wu, C Zhang, Y Zhu - Advances in Neural …, 2022 - proceedings.neurips.cc
Is dynamics prediction indispensable for physical reasoning? If so, what kind of roles do the
dynamics prediction modules play during the physical reasoning process? Most studies …

[HTML][HTML] A reconfigurable data glove for reconstructing physical and virtual grasps

H Liu, Z Zhang, Z Jiao, Z Zhang, M Li, C Jiang, Y Zhu… - Engineering, 2024 - Elsevier
In this work, we present a reconfigurable data glove design to capture different modes of
human hand–object interactions, which are critical in training embodied artificial intelligence …

Understanding physical effects for effective tool-use

Z Zhang, Z Jiao, W Wang, Y Zhu… - IEEE Robotics and …, 2022 - ieeexplore.ieee.org
We present a robot learning and planning framework that produces an effective tool-use
strategy with the least joint efforts, capable of handling objects different from training …