Zobrazeno 1 - 10
of 69
pro vyhledávání: '"Melnik, Andrew"'
Autor:
Yenamandra, Sriram, Ramachandran, Arun, Khanna, Mukul, Yadav, Karmesh, Vakil, Jay, Melnik, Andrew, Büttner, Michael, Harz, Leon, Brown, Lyon, Nandi, Gora Chand, PS, Arjun, Yadav, Gaurav Kumar, Kala, Rahul, Haschke, Robert, Luo, Yang, Zhu, Jinxin, Han, Yansen, Lu, Bingyi, Gu, Xuan, Liu, Qinyuan, Zhao, Yaping, Ye, Qiting, Dou, Chenxiao, Chua, Yansong, Kuzma, Volodymyr, Humennyy, Vladyslav, Partsey, Ruslan, Francis, Jonathan, Chaplot, Devendra Singh, Chhablani, Gunjan, Clegg, Alexander, Gervet, Theophile, Jain, Vidhi, Ramrakhya, Ram, Szot, Andrew, Wang, Austin, Yang, Tsung-Yen, Edsinger, Aaron, Kemp, Charlie, Shah, Binit, Kira, Zsolt, Batra, Dhruv, Mottaghi, Roozbeh, Bisk, Yonatan, Paxton, Chris
In order to develop robots that can effectively serve as versatile and capable home assistants, it is crucial for them to reliably perceive and interact with a wide variety of objects across diverse environments. To this end, we proposed Open Vocabul
Externí odkaz:
http://arxiv.org/abs/2407.06939
Diffusion generative models have recently become a robust technique for producing and modifying coherent, high-quality video. This survey offers a systematic overview of critical elements of diffusion models for video generation, covering application
Externí odkaz:
http://arxiv.org/abs/2405.03150
The lane graph is a key component for building high-definition (HD) maps and crucial for downstream tasks such as autonomous driving or navigation planning. Previously, He et al. (2022) explored the extraction of the lane-level graph from aerial imag
Externí odkaz:
http://arxiv.org/abs/2405.00620
Recent advancements in Generative Artificial Intelligence, particularly in the realm of Large Language Models (LLMs) and Large Vision Language Models (LVLMs), have enabled the prospect of leveraging cognitive planners within robotic systems. This wor
Externí odkaz:
http://arxiv.org/abs/2404.00318
We demonstrate experimental results with LLMs that address robotics task planning problems. Recently, LLMs have been applied in robotics task planning, particularly using a code generation approach that converts complex high-level instructions into m
Externí odkaz:
http://arxiv.org/abs/2403.13801
Behavioral cloning uses a dataset of demonstrations to learn a policy. To overcome computationally expensive training procedures and address the policy adaptation problem, we propose to use latent spaces of pre-trained foundation models to index a de
Externí odkaz:
http://arxiv.org/abs/2401.16398
Autor:
Melnik, Andrew, Schiewer, Robin, Lange, Moritz, Muresanu, Andrei, Saeidi, Mozhgan, Garg, Animesh, Ritter, Helge
Physical reasoning is a crucial aspect in the development of general AI systems, given that human learning starts with interacting with the physical world before progressing to more complex concepts. Although researchers have studied and assessed the
Externí odkaz:
http://arxiv.org/abs/2312.10728
Autor:
Melnik, Andrew, Büttner, Michael, Harz, Leon, Brown, Lyon, Nandi, Gora Chand, PS, Arjun, Yadav, Gaurav Kumar, Kala, Rahul, Haschke, Robert
This report introduces our UniTeam agent - an improved baseline for the "HomeRobot: Open Vocabulary Mobile Manipulation" challenge. The challenge poses problems of navigation in unfamiliar environments, manipulation of novel objects, and recognition
Externí odkaz:
http://arxiv.org/abs/2312.08611
Reinforcement learning and Imitation Learning approaches utilize policy learning strategies that are difficult to generalize well with just a few examples of a task. In this work, we propose a language-conditioned semantic search-based method to prod
Externí odkaz:
http://arxiv.org/abs/2312.05925
Behavioural cloning uses a dataset of demonstrations to learn a behavioural policy. To overcome various learning and policy adaptation problems, we propose to use latent space to index a demonstration dataset, instantly access similar relevant experi
Externí odkaz:
http://arxiv.org/abs/2306.09082