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检索条件"机构=Computational Learning and Motor Control"
70 条 记 录,以下是41-50 订阅
排序:
Leveraging big data for grasp planning
Leveraging big data for grasp planning
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IEEE International Conference on Robotics and Automation (ICRA)
作者: Daniel Kappler Jeannette Bohg Stefan Schaal Autonomous Motion Department at the Max-Planck-Institute for Intelligent Systems Tübingen Germany Computational Learning and Motor Control lab at the University of Southern California Los Angeles CA USA
We propose a new large-scale database containing grasps that are applied to a large set of objects from numerous categories. These grasps are generated in simulation and are annotated with different grasp stability me... 详细信息
来源: 评论
Inverse kinematics for humanoid robots
Inverse kinematics for humanoid robots
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IEEE International Conference on Robotics and Automation (ICRA)
作者: G. Tevatia S. Schaal Kawato Dynamic Brain Project ERATO Japan Science and Technology Agency Kyoto Japan Computational Learning and Motor Control Laboratory University of Southern California Los Angeles CA USA
Real-time control of the end-effector of a humanoid robot in external coordinates requires computationally efficient solutions of the inverse kinematics problem. In this context, this paper investigates methods of res... 详细信息
来源: 评论
Parameter learning for improving binary descriptor matching
Parameter learning for improving binary descriptor matching
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IEEE/RSJ International Conference on Intelligent Robots and Systems
作者: Bharath Sankaran Srikumar Ramalingam Yuichi Taguchi Computational Learning and Motor Control Lab University of Southern California Los Angeles 90089 United States of America Mitsubishi Electric Research Labs Cambridge MA 02139 United States of America
Binary descriptors allow fast detection and matching algorithms in computer vision problems. Though binary descriptors can be computed at almost two orders of magnitude faster than traditional gradient based descripto... 详细信息
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Dependence of orientation tuning on recurrent excitation and inhibition in a network model of V1
Dependence of orientation tuning on recurrent excitation and...
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22nd Annual Conference on Neural Information Processing Systems, NIPS 2008
作者: Wimmer, Klaus Stimberg, Marcel Martin, Robert Schwabe, Lars Mariño, Jorge Schummers, James Lyon, David C. Sur, Mriganka Obermayer, Klaus Bernstein Center for Computational Neuroscience Technische Universität Berlin Germany Dept of Computer Science and Electrical Engineering University of Rostock Germany Dept of Medicine Neuroscience and Motor Control Group Univ. A Coruña Spain Dept of Brain and Cognitive Sci Picower Ctr for Learning and Memory MIT Cambridge United States Dept of Anatomy and Neurobiology University of California Irvine United States
The computational role of the local recurrent network in primary visual cortex is still a matter of debate. To address this issue, we analyze intracellular recording data of cat V1, which combine measuring the tuning ... 详细信息
来源: 评论
Probabilistic Recurrent State-Space Models
arXiv
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arXiv 2018年
作者: Doerr, Andreas Daniel, Christian Schiegg, Martin Nguyen-Tuong, Duy Schaal, Stefan Toussaint, Marc Trimpe, Sebastian Bosch Center for Artificial Intelligence Renningen Germany Max Planck Institute for Intelligent Systems Stuttgart/Tübingen Germany Computational Learning and Motor Control Lab University of Southern California United States Machine Learning and Robotics Lab University of Stuttgart Germany
State-space models (SSMs) are a highly expressive model class for learning patterns in time series data and for system identification. Deterministic versions of SSMs (e.g. LSTMs) proved extremely successful in modelin... 详细信息
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Reinforcement learning of impedance control in stochastic force fields
Reinforcement learning of impedance control in stochastic fo...
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IEEE International Conference on Development and learning, ICDL
作者: Freek Stulp Jonas Buchli Alice Ellmer Michael Mistry Evangelos Theodorou Stefan Schaal Computational Learning and Motor Control Laboratory University of Southern California Los Angeles CA USA Department of Advanced Robotics Italian Institute of Technology Genova Italy Disney Research Pittsburgh PA USA
Variable impedance control is essential for ensuring robust and safe physical interaction with the environment. As demonstrated in numerous force field experiments, humans combine two strategies to adapt their impedan... 详细信息
来源: 评论
Robot arm pose estimation through pixel-wise part classification
Robot arm pose estimation through pixel-wise part classifica...
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IEEE International Conference on Robotics and Automation (ICRA)
作者: Jeannette Bohg Javier Romero Alexander Herzog Stefan Schaal Autonomous Motion Department Perceiving Systems Max-Planck-Institute for Intelligent Systems Tübingen Germany Computational Learning and Motor Control lab University of Southern California Los Angeles CA USA
We propose to frame the problem of marker-less robot arm pose estimation as a pixel-wise part classification problem. As input, we use a depth image in which each pixel is classified to be either from a particular rob... 详细信息
来源: 评论
Toward simple control for complex, autonomous robotic applications: Combining discrete and rhythmic motor primitives
Toward simple control for complex, autonomous robotic applic...
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作者: Degallier, Sarah Righetti, Ludovic Gay, Sebastien Ijspeert, Auke CNBI Laboratory School of Engineering EPFL Ecole Polytechnique Fédérale de Lausanne Lausanne 1015 Switzerland Biorobotics Laboratory School of Engineering EPFL Ecole Polytechnique Fédérale de Lausanne Lausanne 1015 Switzerland Computational Learning and Motor Control Lab Computer Science Neurosciences and Biomedical Engineering University of Southern California Los Angeles CA 90089 United States
Vertebrates are able to quickly adapt to new environments in a very robust, seemingly effortless way. To explain both this adaptivity and robustness, a very promising perspective in neurosciences is the modular approa... 详细信息
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control of legged robots with optimal distribution of contact forces
Control of legged robots with optimal distribution of contac...
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IEEE-RAS International Conference on Humanoid Robots
作者: Ludovic Righetti Jonas Buchli Michael Mistry Stefan Schaal Computational Learning and Motor Control Laboratory University of Southern California Los Angeles CA USA Department of Advanced Robotics Italian Institute of Technology Genova Italy Disney Research Pittsburgh Pittsburgh PA USA
The development of agile and safe humanoid robots require controllers that guarantee both high tracking performance and compliance with the environment. More specifically, the control of contact interaction is of cruc... 详细信息
来源: 评论
Combining learned and analytical models for predicting action effects from sensory data
arXiv
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arXiv 2017年
作者: Kloss, Alina Schaal, Stefan Bohg, Jeannette Autonomous Motion Department Max Planck Institute for Intelligent Systems Germany Computational Learning and Motor Control Lab University of Southern California United States Department of Computer Science Stanford University United States
One of the most basic skills a robot should possess is predicting the effect of physical interactions with objects in the environment. This enables optimal action selection to reach a certain goal state. Traditionally... 详细信息
来源: 评论