Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Mosbach, Malte"'
Learning a latent dynamics model provides a task-agnostic representation of an agent's understanding of its environment. Leveraging this knowledge for model-based reinforcement learning holds the potential to improve sample efficiency over model-free
Externí odkaz:
http://arxiv.org/abs/2410.08822
Autor:
Mosbach, Malte, Behnke, Sven
Interactive grasping from clutter, akin to human dexterity, is one of the longest-standing problems in robot learning. Challenges stem from the intricacies of visual perception, the demand for precise motor skills, and the complex interplay between t
Externí odkaz:
http://arxiv.org/abs/2403.10187
Autor:
Mosbach, Malte, Behnke, Sven
Tool use, a hallmark feature of human intelligence, remains a challenging problem in robotics due the complex contacts and high-dimensional action space. In this work, we present a novel method to enable reinforcement learning of tool use behaviors.
Externí odkaz:
http://arxiv.org/abs/2307.16499
Publikováno v:
2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids) 435-441
Dexterous manipulation with anthropomorphic robot hands remains a challenging problem in robotics because of the high-dimensional state and action spaces and complex contacts. Nevertheless, skillful closed-loop manipulation is required to enable huma
Externí odkaz:
http://arxiv.org/abs/2212.02126
Autor:
Mosbach, Malte, Behnke, Sven
Grasping objects of different shapes and sizes - a foundational, effortless skill for humans - remains a challenging task in robotics. Although model-based approaches can predict stable grasp configurations for known object models, they struggle to g
Externí odkaz:
http://arxiv.org/abs/2211.10957
Autor:
Mosbach, Malte, Behnke, Sven
The ability to predict future outcomes conditioned on observed video frames is crucial for intelligent decision-making in autonomous systems. Recently, deep recurrent architectures have been applied to the task of video prediction. However, this ofte
Externí odkaz:
http://arxiv.org/abs/2110.05881