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检索条件"机构=Machine Learning and Robotics Lab University of Stuttgart"
147 条 记 录,以下是91-100 订阅
排序:
learning arbitration for shared autonomy by hindsight data aggregation
arXiv
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arXiv 2019年
作者: Oh, Yoojin Toussaint, Marc Mainprice, Jim Machine Learning and Robotics Lab University of Stuttgart Germany Max Planck Institute for Intelligent Systems MPI-IS Tübingen Germany
In this paper we present a framework for the teleoperation of pick-and-place tasks. We define a shared control policy that allows to blend between direct user control and autonomous control based on user intent infere... 详细信息
来源: 评论
Prediction of human full-body movements with motion optimization and recurrent neural networks
arXiv
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arXiv 2019年
作者: Kratzer, Philipp Toussaint, Marc Mainprice, Jim Machine Learning and Robotics Lab University of Stuttgart Germany Max Planck Institute for Intelligent Systems IS-MPI Tübingen Germany
Human movement prediction is difficult as humans naturally exhibit complex behaviors that can change drastically from one environment to the next. In order to alleviate this issue, we propose a prediction framework th... 详细信息
来源: 评论
Deep workpiece region segmentation for bin picking
arXiv
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arXiv 2019年
作者: Khalid, Muhammad Usman Hager, Janik M. Kraus, Werner Huber, Marco F. Toussaint, Marc Robot and Assistive Systems Fraunhofer IPA Stuttgart Germany Machine Learning & Robotics Lab University of Stuttgart Germany Fraunhofer IPA Stuttgart and Institute of Industrial Manufacturing and Management IFF University of Stuttgart Germany
For most industrial bin picking solutions, the pose of a workpiece is localized by matching a CAD model to point cloud obtained from 3D sensor. Distinguishing flat workpieces from bottom of the bin in point cloud impo... 详细信息
来源: 评论
Trajectory-based off-policy deep reinforcement learning
arXiv
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arXiv 2019年
作者: Doerr, Andreas Volpp, Michael Toussaint, Marc Trimpe, Sebastian Daniel, Christian Bosch Center for Artificial Intelligence Renningen Germany Max Planck Institute for Intelligent Systems Stuttgart/Tubingen Germany Machine Learning and Robotics Lab University of Stuttgart Germany
Policy gradient methods are powerful reinforcement learning algorithms and have been demonstrated to solve many complex tasks. However, these methods are also data-inefficient, afflicted with high variance gradient es... 详细信息
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Bayesian Model Selection of Lithium-Ion Battery Models via Bayesian Quadrature
arXiv
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arXiv 2022年
作者: Adachi, Masaki Kuhn, Yannick Horstmann, Birger Osborne, Michael A. Howey, David A. Machine Learning Research Group University of Oxford OX2 6ED United Kingdom Battery Intelligence Lab University of Oxford OX1 3PJ United Kingdom Pfaffenwaldring 38-40 Stuttgart70569 Germany Helmholtz Institute Ulm Helmholtzstraße 11 Ulm89081 Germany Universität Ulm Albert-Einstein-Allee 47 Ulm89081 Germany The Faraday Institution Harwell Campus DidcotOX11 0RA United Kingdom
This paper presents a Bayesian model selection approach via Bayesian quadrature and sensitivity analysis of the selection criterion for a lithium-ion battery model. The Bayesian model evidence is adopted as the metric... 详细信息
来源: 评论
Prior Visual Relationship Reasoning For Visual Question Answering
Prior Visual Relationship Reasoning For Visual Question Answ...
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IEEE International Conference on Image Processing
作者: Zhuoqian Yang Zengchang Qin Jing Yu Tao Wan Robotics Institute Carnegie Mellon University Pittsburgh PA USA Intelligent Computing and Machine Learning Lab School of ASEE Beihang University China Institute of Information Engineering CAS China School of Biological Science and Medical Engineering Beihang University Beijing China
Visual Question Answering (VQA) is a representative task of cross-modal reasoning where an image and a free-form question in natural language are presented and the correct answer needs to be determined using both visu... 详细信息
来源: 评论
Kinematic morphing networks for manipulation skill transfer
arXiv
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arXiv 2018年
作者: Englert, Peter Toussaint, Marc Machine Learning & Robotics Lab University of Stuttgart Germany
The transfer of a robot skill between different geometric environments is non-trivial since a wide variety of environments exists, sensor observations as well as robot motions are high-dimensional, and the environment... 详细信息
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Constrained Bayesian optimization of combined interaction force/task space controllers for manipulations
Constrained Bayesian optimization of combined interaction fo...
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2017 IEEE International Conference on robotics and Automation, ICRA 2017
作者: Dries, Danny Englert, Peter Toussaint, Marc Machine Learning and Robotics Lab University of Stuttgart Germany
In this paper, we address the problem of how a robot can optimize parameters of combined interaction force/task space controllers under a success constraint in an active way. To enable the robot to explore its environ... 详细信息
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Deep learning Approach for Linear Locomotion Control of Spherical Robot
Deep Learning Approach for Linear Locomotion Control of Sphe...
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International Conference on Control, Automation and Systems ( ICCAS)
作者: Daniel W Nam Chaehyeuk Lee Jaehwan Choi Yeonjun Kim Soon-Geul Lee KC Machine Learning Lab (ML2) Seoul Korea Medipixel Seoul Korea HANCOM Robotics Pangyo Korea Kyung Hee University Yongin Korea
Spherical robot is a typical nonlinear underactuated nonholonomic system that is difficult to control accurate path trajectory and uniform and stable posture during transfer. In this paper, we propose a method called ...
来源: 评论
learning to Control Redundant Musculoskeletal Systems with Neural Networks and SQP: Exploiting Muscle Properties
Learning to Control Redundant Musculoskeletal Systems with N...
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IEEE International Conference on robotics and Automation
作者: Danny Driess Heiko Zimmermann Simon Wolfen Dan Suissa Daniel Haeufle Daniel Hennes Marc Toussaint Syn Schmitt Machine Learning and Robotics Lab University of Stuttgart Germany Biomechanics and Biorobotics Group University of Stuttgart Germany Multi-Level Modeling in Motor Control and Rehabilitation Robotics University of Tübingen Germany
Modeling biomechanical musculoskeletal systems reveals that the mapping from muscle stimulations to movement dynamics is highly nonlinear and complex, which makes it difficult to control those systems with classical t... 详细信息
来源: 评论