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Octo: An open-source generalist robot policy
Large policies pretrained on diverse robot datasets have the potential to transform robotic
learning: instead of training new policies from scratch, such generalist robot policies may be …
learning: instead of training new policies from scratch, such generalist robot policies may be …
Robot learning in the era of foundation models: A survey
The proliferation of Large Language Models (LLMs) has s fueled a shift in robot learning
from automation towards general embodied Artificial Intelligence (AI). Adopting foundation …
from automation towards general embodied Artificial Intelligence (AI). Adopting foundation …
Cyberdemo: Augmenting simulated human demonstration for real-world dexterous manipulation
We introduce CyberDemo a novel approach to robotic imitation learning that leverages
simulated human demonstrations for real-world tasks. By incorporating extensive data …
simulated human demonstrations for real-world tasks. By incorporating extensive data …
Robocasa: Large-scale simulation of everyday tasks for generalist robots
Recent advancements in Artificial Intelligence (AI) have largely been propelled by scaling. In
Robotics, scaling is hindered by the lack of access to massive robot datasets. We advocate …
Robotics, scaling is hindered by the lack of access to massive robot datasets. We advocate …
Robotgpt: Robot manipulation learning from chatgpt
We present RobotGPT, an innovative decision framework for robotic manipulation that
prioritizes stability and safety. The execution code generated by ChatGPT cannot guarantee …
prioritizes stability and safety. The execution code generated by ChatGPT cannot guarantee …
: A Vision-Language-Action Flow Model for General Robot Control
Robot learning holds tremendous promise to unlock the full potential of flexible, general, and
dexterous robot systems, as well as to address some of the deepest questions in artificial …
dexterous robot systems, as well as to address some of the deepest questions in artificial …
Transic: Sim-to-real policy transfer by learning from online correction
Learning in simulation and transferring the learned policy to the real world has the potential
to enable generalist robots. The key challenge of this approach is to address simulation-to …
to enable generalist robots. The key challenge of this approach is to address simulation-to …
The colosseum: A benchmark for evaluating generalization for robotic manipulation
To realize effective large-scale, real-world robotic applications, we must evaluate how well
our robot policies adapt to changes in environmental conditions. Unfortunately, a majority of …
our robot policies adapt to changes in environmental conditions. Unfortunately, a majority of …
Echoscene: Indoor scene generation via information echo over scene graph diffusion
We present EchoScene, an interactive and controllable generative model that generates 3D
indoor scenes on scene graphs. EchoScene leverages a dual-branch diffusion model that …
indoor scenes on scene graphs. EchoScene leverages a dual-branch diffusion model that …
Human-in-the-loop task and motion planning for imitation learning
Imitation learning from human demonstrations can teach robots complex manipulation skills,
but is time-consuming and labor intensive. In contrast, Task and Motion Planning (TAMP) …
but is time-consuming and labor intensive. In contrast, Task and Motion Planning (TAMP) …