Zobrazeno 1 - 10
of 743
pro vyhledávání: '"Huang Haojie"'
Many manipulation tasks require the robot to rearrange objects relative to one another. Such tasks can be described as a sequence of relative poses between parts of a set of rigid bodies. In this work, we propose MATCH POLICY, a simple but novel pipe
Externí odkaz:
http://arxiv.org/abs/2409.15517
Autor:
Qian, Yaoyao, Zhu, Xupeng, Biza, Ondrej, Jiang, Shuo, Zhao, Linfeng, Huang, Haojie, Qi, Yu, Platt, Robert
Robotic grasping in cluttered environments remains a significant challenge due to occlusions and complex object arrangements. We have developed ThinkGrasp, a plug-and-play vision-language grasping system that makes use of GPT-4o's advanced contextual
Externí odkaz:
http://arxiv.org/abs/2407.11298
Autor:
Hu, Boce, Zhu, Xupeng, Wang, Dian, Dong, Zihao, Huang, Haojie, Wang, Chenghao, Walters, Robin, Platt, Robert
While grasp detection is an important part of any robotic manipulation pipeline, reliable and accurate grasp detection in $SE(3)$ remains a research challenge. Many robotics applications in unstructured environments such as the home or warehouse woul
Externí odkaz:
http://arxiv.org/abs/2407.03531
Autor:
Wang, Dian, Hart, Stephen, Surovik, David, Kelestemur, Tarik, Huang, Haojie, Zhao, Haibo, Yeatman, Mark, Wang, Jiuguang, Walters, Robin, Platt, Robert
Recent work has shown diffusion models are an effective approach to learning the multimodal distributions arising from demonstration data in behavior cloning. However, a drawback of this approach is the need to learn a denoising function, which is si
Externí odkaz:
http://arxiv.org/abs/2407.01812
Autor:
Jia, Mingxi, Huang, Haojie, Zhang, Zhewen, Wang, Chenghao, Zhao, Linfeng, Wang, Dian, Liu, Jason Xinyu, Walters, Robin, Platt, Robert, Tellex, Stefanie
Controlling robots through natural language instructions in open-vocabulary scenarios is pivotal for enhancing human-robot collaboration and complex robot behavior synthesis. However, achieving this capability poses significant challenges due to the
Externí odkaz:
http://arxiv.org/abs/2406.15677
Autor:
Huang, Haojie, Schmeckpeper, Karl, Wang, Dian, Biza, Ondrej, Qian, Yaoyao, Liu, Haotian, Jia, Mingxi, Platt, Robert, Walters, Robin
Humans can imagine goal states during planning and perform actions to match those goals. In this work, we propose Imagination Policy, a novel multi-task key-frame policy network for solving high-precision pick and place tasks. Instead of learning act
Externí odkaz:
http://arxiv.org/abs/2406.11740
Autor:
Huang, HaoJie
The prime number problem falls within the realm of number theory, specifically elementary number theory. Current research approaches have unnecessarily complicated this matter. In contrast to more advanced mathematical tools, the methods of elementar
Externí odkaz:
http://arxiv.org/abs/2404.02610
Many complex robotic manipulation tasks can be decomposed as a sequence of pick and place actions. Training a robotic agent to learn this sequence over many different starting conditions typically requires many iterations or demonstrations, especiall
Externí odkaz:
http://arxiv.org/abs/2401.12046
Robotic pick and place tasks are symmetric under translations and rotations of both the object to be picked and the desired place pose. For example, if the pick object is rotated or translated, then the optimal pick action should also rotate or trans
Externí odkaz:
http://arxiv.org/abs/2308.07948
Given point cloud input, the problem of 6-DoF grasp pose detection is to identify a set of hand poses in SE(3) from which an object can be successfully grasped. This important problem has many practical applications. Here we propose a novel method an
Externí odkaz:
http://arxiv.org/abs/2211.00191