Zobrazeno 1 - 10
of 167
pro vyhledávání: '"Haschke, Robert"'
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
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
Tactile information is important for robust performance in robotic tasks that involve physical interaction, such as object manipulation. However, with more data included in the reasoning and control process, modeling behavior becomes increasingly dif
Externí odkaz:
http://arxiv.org/abs/2311.07260
We present a holistic grasping controller, combining free-space position control and in-contact force-control for reliable grasping given uncertain object pose estimates. Employing tactile fingertip sensors, undesired object displacement during grasp
Externí odkaz:
http://arxiv.org/abs/2311.07257
Autor:
Lach, Luca, Haschke, Robert, Tateo, Davide, Peters, Jan, Ritter, Helge, Borràs, Júlia, Torras, Carme
The advent of tactile sensors in robotics has sparked many ideas on how robots can leverage direct contact measurements of their environment interactions to improve manipulation tasks. An important line of research in this regard is that of grasp for
Externí odkaz:
http://arxiv.org/abs/2311.07245
Autor:
Lach, Luca, Funk, Niklas, Haschke, Robert, Lemaignan, Severin, Ritter, Helge Joachim, Peters, Jan, Chalvatzaki, Georgia
This work deals with a practical everyday problem: stable object placement on flat surfaces starting from unknown initial poses. Common object-placing approaches require either complete scene specifications or extrinsic sensor measurements, e.g., cam
Externí odkaz:
http://arxiv.org/abs/2210.02054
Despite many advances in service robotics, successful and secure object manipulation on mobile platforms is still a challenge. In order to come closer to human grasping performance, it is natural to provide robots with the same capability that humans
Externí odkaz:
http://arxiv.org/abs/2010.10810
When data are organized in matrices or arrays of higher dimensions (tensors), classical regression methods first transform these data into vectors, therefore ignoring the underlying structure of the data and increasing the dimensionality of the probl
Externí odkaz:
http://arxiv.org/abs/1902.11104