Výsledky vyhledávání - "Görner, Michael"

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RoboGolf: Mastering Real-World Minigolf with a Reflective Multi-Modality Vision-Language Model

Autor: Zhou, Hantao, Ji, Tianying, Sommerhalder, Lukas, Goerner, Michael, Hendrich, Norman, Zhang, Jianwei, Sun, Fuchun, Xu, Huazhe

Minigolf is an exemplary real-world game for examining embodied intelligence, requiring challenging spatial and kinodynamic understanding to putt the ball. Additionally, reflective reasoning is required if the feasibility of a challenge is not ensure

Externí odkaz: http://arxiv.org/abs/2406.10157

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Self-Adapting Recurrent Models for Object Pushing from Learning in Simulation

Autor: Cong, Lin, Görner, Michael, Ruppel, Philipp, Liang, Hongzhuo, Hendrich, Norman, Zhang, Jianwei

Planar pushing remains a challenging research topic, where building the dynamic model of the interaction is the core issue. Even an accurate analytical dynamic model is inherently unstable because physics parameters such as inertia and friction can o

Externí odkaz: http://arxiv.org/abs/2007.13421

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Vision-based Teleoperation of Shadow Dexterous Hand using End-to-End Deep Neural Network

Autor: Li, Shuang, Ma, Xiaojian, Liang, Hongzhuo, Görner, Michael, Ruppel, Philipp, Fang, Bing, Sun, Fuchun, Zhang, Jianwei

In this paper, we present TeachNet, a novel neural network architecture for intuitive and markerless vision-based teleoperation of dexterous robotic hands. Robot joint angles are directly generated from depth images of the human hand that produce vis

Externí odkaz: http://arxiv.org/abs/1809.06268

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PointNetGPD: Detecting Grasp Configurations from Point Sets

Autor: Liang, Hongzhuo, Ma, Xiaojian, Li, Shuang, Görner, Michael, Tang, Song, Fang, Bin, Sun, Fuchun, Zhang, Jianwei

In this paper, we propose an end-to-end grasp evaluation model to address the challenging problem of localizing robot grasp configurations directly from the point cloud. Compared to recent grasp evaluation metrics that are based on handcrafted depth

Externí odkaz: http://arxiv.org/abs/1809.06267

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