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检索条件"机构=The Learning Systems and Robotics Lab"
118 条 记 录,以下是71-80 订阅
排序:
Natural gradient shared control
arXiv
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arXiv 2020年
作者: Oh, Yoojin Wu, Shao-Wen Toussaint, Marc Mainprice, Jim Machine Learning and Robotics Lab University of Stuttgart Germany Learning and Intelligent Systems Lab TU Berlin Berlin Germany Max Planck Institute for Intelligent Systems IS-MPI Tübingen Germany
We propose a formalism for shared control, which is the problem of defining a policy that blends user control and autonomous control. The challenge posed by the shared autonomy system is to maintain user control autho... 详细信息
来源: 评论
An Interior Point Method Solving Motion Planning Problems with Narrow Passages
arXiv
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arXiv 2020年
作者: Mainprice, Jim Ratliff, Nathan Toussaint, Marc Schaal, Stefan Machine Learning and Robotics Lab University of Stuttgart Germany Max Planck Institute for Intelligent Systems IS-MPITübingen & Stuttgart Germany Learning and Intelligent Systems Lab TU Berlin Berlin Germany
Algorithmic solutions for the motion planning problem have been investigated for five decades. Since the development of A* in 1969 many approaches have been investigated, traditionally classified as either grid decomp... 详细信息
来源: 评论
PandaNet: Anchor-Based Single-Shot Multi-Person 3D Pose Estimation
PandaNet: Anchor-Based Single-Shot Multi-Person 3D Pose Esti...
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Conference on Computer Vision and Pattern Recognition (CVPR)
作者: Abdallah Benzine Florian Chabot Bertrand Luvison Quoc Cuong Pham Catherine Achard CEA LIST Vision and Learning Lab for Scene Analysis Sorbonne University CNRS Institute for Intelligent Systems and Robotics
Recently, several deep learning models have been proposed for 3D human pose estimation. Nevertheless, most of these approaches only focus on the single-person case or estimate 3D pose of a few people at high resolutio... 详细信息
来源: 评论
An Interior Point Method Solving Motion Planning Problems with Narrow Passages
An Interior Point Method Solving Motion Planning Problems wi...
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IEEE International Workshop on Robot and Human Communication (ROMAN)
作者: Jim Mainprice Nathan Ratliff Marc Toussaint Stefan Schaal Machine Learning and Robotics Lab University of Stuttgart Germany Max Planck Institute for Intelligent Systems IS-MPI Tübingen & Stuttgart Germany Learning and Intelligent Systems Lab TU Berlin Berlin Germany
Algorithmic solutions for the motion planning problem have been investigated for five decades. Since the development of A* in 1969 many approaches have been investigated, traditionally classified as either grid decomp...
来源: 评论
Deep Visual Heuristics: learning Feasibility of Mixed-Integer Programs for Manipulation Planning
Deep Visual Heuristics: Learning Feasibility of Mixed-Intege...
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IEEE International Conference on robotics and Automation (ICRA)
作者: Danny Driess Ozgur Oguz Jung-Su Ha Marc Toussaint Machine Learning and Robotics Lab University of Stuttgart Germany Max Planck Institute for Intelligent Systems Stuttgart Germany
In this paper, we propose a deep neural network that predicts the feasibility of a mixed-integer program from visual input for robot manipulation planning. Integrating learning into task and motion planning is challen... 详细信息
来源: 评论
Anticipating Human Intention for Full-Body Motion Prediction in Object Grasping and Placing Tasks
Anticipating Human Intention for Full-Body Motion Prediction...
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IEEE International Workshop on Robot and Human Communication (ROMAN)
作者: Philipp Kratzer Niteesh Balachandra Midlagajni Marc Toussaint Jim Mainprice Machine Learning and Robotics Lab University of Stuttgart Germany Humans to Robots Motions Research Group HRM University of Stuttgart Germany Learning and Intelligent Systems Lab Technical University of Berlin Germany
Motion prediction in unstructured environments is a difficult problem and is essential for safe and efficient human-robot space sharing and collaboration. In this work, we focus on manipulation movements in environmen...
来源: 评论
Anticipating Human Intention for Full-Body Motion Prediction in Object Grasping and Placing Tasks
arXiv
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arXiv 2020年
作者: Kratzer, Philipp Midlagajni, Niteesh Balachandra Toussaint, Marc Mainprice, Jim Machine Learning and Robotics Lab University of Stuttgart Germany Humans to Robots Motions Research Group HRM University of Stuttgart Germany Learning and Intelligent Systems Lab Technical University of Berlin Germany
Motion prediction in unstructured environments is a difficult problem and is essential for safe and efficient human-robot space sharing and collaboration. In this work, we focus on manipulation movements in environmen... 详细信息
来源: 评论
Describing Physics For Physical Reasoning: Force-based Sequential Manipulation Planning
arXiv
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arXiv 2020年
作者: Toussaint, Marc Ha, Jung-Su Driess, Danny Machine Learning & Robotics Lab University Stuttgart Stuttgart70569 Germany Max Planck Institute for Intelligent Systems Stuttgart70569 Germany
Physical reasoning is a core aspect of intelligence in animals and humans. A central question is what model should be used as a basis for reasoning. Existing work considered models ranging from intuitive physics and p...
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Motion planner augmented reinforcement learning for robot manipulation in obstructed environments
arXiv
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arXiv 2020年
作者: Yamada, Jun Lee, Youngwoon Salhotra, Gautam Pertsch, Karl Pflueger, Max Sukhatme, Gaurav S. Lim, Joseph J. Englert, Peter Cognitive Learning for Vision and Robotics Lab United States Robotic Embedded Systems Laboratory Department of Computer Science University of Southern California United States
Deep reinforcement learning (RL) agents are able to learn contact-rich manipulation tasks by maximizing a reward signal, but require large amounts of experience, especially in environments with many obstacles that com... 详细信息
来源: 评论
MoGaze: A dataset of full-body motions that includes workspace geometry and eye-gaze
arXiv
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arXiv 2020年
作者: Kratzer, Philipp Bihlmaier, Simon Midlagajni, Niteesh Balachandra Prakash, Rohit Toussaint, Marc Mainprice, Jim Machine Learning and Robotics Lab University of Stuttgart Humans to Robots Motions Research Group University of Stuttgart Germany Humans to Robots Motions Research Group University of Stuttgart Germany Learning and Intelligent Systems lab TU Berlin Germany
As robots become more present in open human environments, it will become crucial for robotic systems to understand and predict human motion. Such capabilities depend heavily on the quality and availability of motion c... 详细信息
来源: 评论