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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31-40 订阅
排序:
Path-Tree Optimization in Discrete Partially Observable Environments using Rapidly-Exploring Belief-Space Graphs
arXiv
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arXiv 2022年
作者: Phiquepal, Camille Orthey, Andreas Viennot, Nicolas Toussaint, Marc Machine Learning & Robotic Lab University of Stuttgart Germany Learning and Intelligent Systems Lab TU Berlin Germany
Robots often need to solve path planning problems where essential and discrete aspects of the environment are partially observable. This introduces a multi-modality, where the robot must be able to observe and infer t... 详细信息
来源: 评论
Physically-Consistent Parameter Identification of Robots in Contact
arXiv
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arXiv 2024年
作者: Khorshidi, Shahram Dawood, Murad Nederkorn, Benno Bennewitz, Maren Khadiv, Majid Humanoid Robots Lab University of Bonn Germany Lamarr Institute for Machine Learning and Artificial Intelligence the Center for Robotics Bonn Germany Roboverse Reply Munich Germany Germany
Accurate inertial parameter identification is crucial for the simulation and control of robots encountering intermittent contacts with the environment. Classically, robots’ inertial parameters are obtained from CAD m... 详细信息
来源: 评论
learning a Shape-Conditioned Agent for Purely Tactile In-Hand Manipulation of Various Objects
Learning a Shape-Conditioned Agent for Purely Tactile In-Han...
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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
作者: Johannes Pitz Lennart Röstel Leon Sievers Darius Burschka Berthold Bäuml Learning AI for Dextrous Robots Lab (***) Technical University of Munich Germany DLR Institute of Robotics & Mechatronics (German Aerospace Center) Machine Vision and Perception Group Technical University of Munich
Reorienting diverse objects with a multi-fingered hand is a challenging task. Current methods in robotic in-hand manipulation are either object-specific or require permanent supervision of the object state from visual... 详细信息
来源: 评论
Safe Leaf Manipulation for Accurate Shape and Pose Estimation of Occluded Fruits
arXiv
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arXiv 2024年
作者: Yao, Shaoxiong Pan, Sicong Bennewitz, Maren Hauser, Kris University of Illinois at Urbana-Champaign IL United States Humanoid Robots Lab University of Bonn Germany Lamarr Institute for Machine Learning and Artificial Intelligence The Center for Robotics Bonn Germany
Fruit monitoring plays an important role in crop management, and rising global fruit consumption combined with labor shortages necessitates automated monitoring with robots. However, occlusions from plant foliage ofte... 详细信息
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Target-Aware Implicit Mapping for Agricultural Crop Inspection
Target-Aware Implicit Mapping for Agricultural Crop Inspecti...
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IEEE International Conference on robotics and Automation (ICRA)
作者: Shane Kelly Alessandro Riccardi Elias Marks Federico Magistri Tiziano Guadagnino Margarita Chli Cyrill Stachniss Vision for Robotics Lab ETH Zurich University of Bonn Lamarr Institute for Machine Learning and Artificial Intelligence Germany Department of Engineering Science University of Oxford UK
Crop inspection is a critical part of modern agricultural practices that helps farmers assess the current status of a field and then make crop management decisions. Current crop inspection methods are labour-intensive...
来源: 评论
learning to execute: efficiently learning universal plan-conditioned policies in robotics  21
Learning to execute: efficiently learning universal plan-con...
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Proceedings of the 35th International Conference on Neural Information Processing Systems
作者: Ingmar Schubert Danny Driess Ozgur S. Oguz Marc Toussaint Learning and Intelligent Systems Group TU Berlin Germany Machine Learning and Robotics Lab University of Stuttgart Germany
Applications of Reinforcement learning (RL) in robotics are often limited by high data demand. On the other hand, approximate models are readily available in many robotics scenarios, making model-based approaches like...
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learning to execute: Efficiently learning universal plan-conditioned policies in robotics
arXiv
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arXiv 2021年
作者: Schubert, Ingmar Driess, Danny Oguz, Ozgur S. Toussaint, Marc Learning and Intelligent Systems Group Tu Berlin Germany Machine Learning and Robotics Lab University of Stuttgart Germany
Applications of Reinforcement learning (RL) in robotics are often limited by high data demand. On the other hand, approximate models are readily available in many robotics scenarios, making model-based approaches like... 详细信息
来源: 评论
Accurate Kinematic Modeling using Autoencoders on Differentiable Joints
Accurate Kinematic Modeling using Autoencoders on Differenti...
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IEEE International Conference on robotics and Automation (ICRA)
作者: Nikolas Wilhelm Sami Haddadin Rainer Burgkart Patrick Van Der Smagt Maximilian Karl Munich Institute of Robotics and Machine Intelligence Technical University of Munich Munich Germany Department of Orthopedics and Sports Orthopedics Klinikum Rechts der Isar School of Medicine Munich Germany Volkswagen Group Machine Learning Research Lab Munich Germany
In robotics and biomechanics, accurately determining joint parameters and computing the corresponding forward and inverse kinematics are critical yet often challenging tasks, especially when dealing with highly indivi... 详细信息
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Deep 6-DoF Tracking of Unknown Objects for Reactive Grasping
Deep 6-DoF Tracking of Unknown Objects for Reactive Grasping
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IEEE International Conference on robotics and Automation (ICRA)
作者: Marc Tuscher Julian Hörz Danny Driess Marc Toussaint sereact Machine Learning and Robotics Lab University of Stuttgart Max-Planck Institute for Intelligent Systems Stuttgart Learning and Intelligent Systems TU Berlin
Robotic manipulation of unknown objects is an important field of research. Practical applications occur in many real-world settings where robots need to interact with an unknown environment. We tackle the problem of r... 详细信息
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Design and Implementation of a Robotic Testbench for Analyzing Pincer Grip Execution in Human Specimen Hands
Design and Implementation of a Robotic Testbench for Analyzi...
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IEEE International Conference on robotics and Automation (ICRA)
作者: Nikolas Wilhelm Claudio Glowalla Sami Haddadin Julian Schote Hannes Höppner Patrick van der Smagt Maximilian Karl Rainer Burgkart Department of Orthopedics and Sports Orthopedics Klinikum Rechts der Isar School of Medicine Munich Germany Munich Institute of Robotics and Machine Intelligence Technical University of Munich Munich Germany Humanoid Robotics Laboratory Berliner Hochschule für Technik Berlin Germany Machine Learning Research Lab Volkswagen Group Munich Germany
This study presents an innovative test rig engineered to explore the kinematic and viscoelastic characteristics of human specimen hands. The rig features eight force-controlled motors linked to muscle tendons, enablin... 详细信息
来源: 评论