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Deep learning approaches to grasp synthesis: A review
Gras** is the process of picking up an object by applying forces and torques at a set of
contacts. Recent advances in deep learning methods have allowed rapid progress in robotic …
contacts. Recent advances in deep learning methods have allowed rapid progress in robotic …
[HTML][HTML] Artificial Intelligence in manufacturing: State of the art, perspectives, and future directions
Inspired by the natural intelligence of humans and bio-evolution, Artificial Intelligence (AI)
has seen accelerated growth since the beginning of the 21st century. Successful AI …
has seen accelerated growth since the beginning of the 21st century. Successful AI …
Foundationpose: Unified 6d pose estimation and tracking of novel objects
We present FoundationPose a unified foundation model for 6D object pose estimation and
tracking supporting both model-based and model-free setups. Our approach can be instantly …
tracking supporting both model-based and model-free setups. Our approach can be instantly …
Bundlesdf: Neural 6-dof tracking and 3d reconstruction of unknown objects
We present a near real-time (10Hz) method for 6-DoF tracking of an unknown object from a
monocular RGBD video sequence, while simultaneously performing neural 3D …
monocular RGBD video sequence, while simultaneously performing neural 3D …
Megapose: 6d pose estimation of novel objects via render & compare
We introduce MegaPose, a method to estimate the 6D pose of novel objects, that is, objects
unseen during training. At inference time, the method only assumes knowledge of (i) a …
unseen during training. At inference time, the method only assumes knowledge of (i) a …
Language-driven grasp detection
Grasp detection is a persistent and intricate challenge with various industrial applications.
Recently many methods and datasets have been proposed to tackle the grasp detection …
Recently many methods and datasets have been proposed to tackle the grasp detection …
You only demonstrate once: Category-level manipulation from single visual demonstration
Promising results have been achieved recently in category-level manipulation that
generalizes across object instances. Nevertheless, it often requires expensive real-world …
generalizes across object instances. Nevertheless, it often requires expensive real-world …
One-shot transfer of affordance regions? affcorrs!
In this work, we tackle one-shot visual search of object parts. Given a single reference image
of an object with annotated affordance regions, we segment semantically corresponding …
of an object with annotated affordance regions, we segment semantically corresponding …
Grasp-anything: Large-scale grasp dataset from foundation models
Foundation models such as ChatGPT have made significant strides in robotic tasks due to
their universal representation of real-world domains. In this paper, we leverage foundation …
their universal representation of real-world domains. In this paper, we leverage foundation …
SimPLE, a visuotactile method learned in simulation to precisely pick, localize, regrasp, and place objects
Existing robotic systems have a tension between generality and precision. Deployed
solutions for robotic manipulation tend to fall into the paradigm of one robot solving a single …
solutions for robotic manipulation tend to fall into the paradigm of one robot solving a single …