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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 …
Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration0
A O'Neill, A Rehman, A Maddukuri… - … on Robotics and …, 2024 - ieeexplore.ieee.org
Large, high-capacity models trained on diverse datasets have shown remarkable successes
on efficiently tackling downstream applications. In domains from NLP to Computer Vision …
on efficiently tackling downstream applications. In domains from NLP to Computer Vision …
[HTML][HTML] Robotic disassembly for end-of-life products focusing on task and motion planning: A comprehensive survey
ME Asif, A Rastegarpanah, R Stolkin - Journal of Manufacturing Systems, 2024 - Elsevier
The rise of mass production and the resulting accumulation of end-of-life (EoL) products
present a growing challenge in waste management and highlight the need for efficient …
present a growing challenge in waste management and highlight the need for efficient …
Lotus: Continual imitation learning for robot manipulation through unsupervised skill discovery
We introduce LOTUS, a continual imitation learning algorithm that empowers a physical
robot to continuously and efficiently learn to solve new manipulation tasks throughout its …
robot to continuously and efficiently learn to solve new manipulation tasks throughout its …
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 …
Prime: Scaffolding manipulation tasks with behavior primitives for data-efficient imitation learning
T Gao, S Nasiriany, H Liu, Q Yang… - IEEE Robotics and …, 2024 - ieeexplore.ieee.org
Imitation learning has shown great potential for enabling robots to acquire complex
manipulation behaviors. However, these algorithms suffer from high sample complexity in …
manipulation behaviors. However, these algorithms suffer from high sample complexity in …
Igor: Image-goal representations are the atomic control units for foundation models in embodied ai
We introduce Image-GOal Representations (IGOR), aiming to learn a unified, semantically
consistent action space across human and various robots. Through this unified latent action …
consistent action space across human and various robots. Through this unified latent action …
Dexskills: Skill segmentation using haptic data for learning autonomous long-horizon robotic manipulation tasks
Effective execution of long-horizon tasks with dexterous robotic hands remains a significant
challenge in real-world problems. While learning from human demonstrations has shown …
challenge in real-world problems. While learning from human demonstrations has shown …
Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning
Reinforcement learning (RL) holds great promise for enabling autonomous acquisition of
complex robotic manipulation skills, but realizing this potential in real-world settings has …
complex robotic manipulation skills, but realizing this potential in real-world settings has …
Cloud-based hierarchical imitation learning for scalable transfer of construction skills from human workers to assisting robots
H Yu, VR Kamat, CC Menassa - Journal of Computing in Civil …, 2024 - ascelibrary.org
Assigning repetitive and physically demanding construction tasks to robots can alleviate
human workers' exposure to occupational injuries, which often result in significant downtime …
human workers' exposure to occupational injuries, which often result in significant downtime …