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Survey of imitation learning for robotic manipulation
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 …
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
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 …
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
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 …
of their soft elastomer from images would yield poor force measurements when the …
A massively parallel and scalable multi-GPU material point method
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 …
simulation system based on the Material Point Method (MPM) for simulating physical …
Scene reconstruction with functional objects for robot autonomy
On the learning mechanisms in physical reasoning
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 …
dynamics prediction modules play during the physical reasoning process? Most studies …
[HTML][HTML] A reconfigurable data glove for reconstructing physical and virtual grasps
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 …
human hand–object interactions, which are critical in training embodied artificial intelligence …
Understanding physical effects for effective tool-use
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 …
strategy with the least joint efforts, capable of handling objects different from training …