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检索条件"机构=The Learning Systems and Robotics lab"
118 条 记 录,以下是31-40 订阅
排序:
A Data-Driven Method for Estimating Formation Flexibility in Beyond-Visual-Range Air Combat
A Data-Driven Method for Estimating Formation Flexibility in...
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International Conference on Unmanned Aircraft systems (ICUAS)
作者: Edvards Scukins Andre N. Costa Petter Ögren Aeronautical Solutions Division SAAB Aeronautics Robotics Perception and Learning Lab. Royal Institute of Technology (KTH) Decision Support Systems Subdivision Institute for Advanced Studies (IEAv)
Tactical decisions in air combat are typically evaluated using experience as a basis. Pilots undergo frequent training in various air combat processes to enhance their combat proficiency and evaluation skills. Having ... 详细信息
来源: 评论
FlowMP: learning Motion Fields for Robot Planning with Conditional Flow Matching
arXiv
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arXiv 2025年
作者: Nguyen, Khang Le, An T. Pham, Tien Huber, Manfred Peters, Jan Vu, Minh Nhat Learning and Adaptive Robotics Lab University of Texas Arlington United States Intelligent Autonomous Systems Lab TU Darmstadt Germany Cognitive Robotics Lab University of Manchester United Kingdom SAIROL Darmstadt Germany Hessian.AI Darmstadt Germany TU Wien Vienna Austria GmbH Vienna Austria
Prior flow matching methods in robotics have primarily learned velocity fields to morph one distribution of trajectories into another. In this work, we extend flow matching to capture second-order trajectory dynamics,... 详细信息
来源: 评论
Augmenting Human Policies using Riemannian Metrics for Human-Robot Shared Control
Augmenting Human Policies using Riemannian Metrics for Human...
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IEEE International Workshop on Robot and Human Communication (ROMAN)
作者: Yoojin Oh Jean-Claude Passy Jim Mainprice Machine Learning and Robotics Lab University of Stuttgart Germany Max Planck Institute for Intelligent Systems Stuttgart Germany Max Planck Institute for Intelligent Systems Tübingen Germany
We present a shared control framework for teleoperation that combines the human and autonomous robot agents operating in different dimension spaces. The shared control problem is an optimization problem to maximize th...
来源: 评论
Keep it Upright: Model Predictive Control for Nonprehensile Object Transportation with Obstacle Avoidance on a Mobile Manipulator
arXiv
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arXiv 2023年
作者: Heins, Adam Schoellig, Angela P. The Learning Systems and Robotics Lab The Technical University of Munich Germany The University of Toronto Institute for Aerospace Studies Canada The Vector Institute for Artificial Intelligence Canada
We consider a nonprehensile manipulation task in which a mobile manipulator must balance objects on its end effector without grasping them-known as the waiter's problem-and move to a desired location while avoidin... 详细信息
来源: 评论
Distilling Motion Planner Augmented Policies into Visual Control Policies for Robot Manipulation  5
Distilling Motion Planner Augmented Policies into Visual Con...
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5th Conference on Robot learning, CoRL 2021
作者: Arthur Liu, I-Chun Uppal, Shagun Sukhatme, Gaurav S. Lim, Joseph J. Englert, Peter Lee, Youngwoon Cognitive Learning for Vision and Robotics Lab University of Southern California United States Robotic Embedded Systems Laboratory University of Southern California United States
learning complex manipulation tasks in realistic, obstructed environments is a challenging problem due to hard exploration in the presence of obstacles and high-dimensional visual observations. Prior work tackles the ... 详细信息
来源: 评论
Probabilistic Spiking Neural Network for Robotic Tactile Continual learning
Probabilistic Spiking Neural Network for Robotic Tactile Con...
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IEEE International Conference on robotics and Automation (ICRA)
作者: Senlin Fang Yiwen Liu Chengliang Liu Jingnan Wang Yuanzhe Su Yupo Zhang Hoiio Kong Zhengkun Yi Xinyu Wu City University of Macau Macau China The Department of Intelligent Systems and Robot Learning Lab ISRL Group SIAT Branch Institute of Artificial Intelligence and Robotics for Society Shenzhen Institute of Advanced Technology Shenzhen
The sense of touch is essential for robots to perform various daily tasks. Artificial Neural Networks have shown significant promise in advancing robotic tactile learning. However, due to the changing of tactile data ... 详细信息
来源: 评论
AMSwarmX: Safe Swarm Coordination in CompleX Environments via Implicit Non-Convex Decomposition of the Obstacle-Free Space
arXiv
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arXiv 2023年
作者: Adajania, Vivek K. Zhou, Siqi Singh, Arun Kumar Schoellig, Angela P. The Learning Systems and Robotics Lab The University of Toronto Institute for Aerospace Studies Canada The Technical University of Munich Germany The Vector Institute for Artificial Intelligence The University of Tartu Estonia
Quadrotor motion planning in complex environments leverage the concept of safe flight corridor (SFC) to facilitate static obstacle avoidance. Typically, SFCs are constructed through convex decomposition of the environ... 详细信息
来源: 评论
AMSwarm: An Alternating Minimization Approach for Safe Motion Planning of Quadrotor Swarms in Cluttered Environments
AMSwarm: An Alternating Minimization Approach for Safe Motio...
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IEEE International Conference on robotics and Automation (ICRA)
作者: Vivek K. Adajania Siqi Zhou Arun Kumar Singh Angela P. Schoellig Learning Systems and Robotics Lab University of Toronto Institute for Aerospace Studies Canada Technical University of Munich Germany Vector Institute for Artificial Intelligence University of Tartu Estonia
This paper presents a scalable online algorithm to generate safe and kinematically feasible trajectories for quadrotor swarms. Existing approaches rely on linearizing Euclidean distance-based collision constraints and...
来源: 评论
Planning Coordinated Human-Robot Motions with Neural Network Full-Body Prediction Models
arXiv
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arXiv 2022年
作者: Kratzer, Philipp Toussaint, Marc Mainprice, Jim The Machine Learning and Robotics Lab University of Stuttgart Germany The Humans to Robots Motions Research Group University of Stuttgart Germany The Learning and Intelligent Systems Lab TU Berlin Germany
Numerical optimization has become a popular approach to plan smooth motion trajectories for robots. However, when sharing space with humans, balancing properly safety, comfort and efficiency still remains challenging.... 详细信息
来源: 评论
AMSwarm: An Alternating Minimization Approach for Safe Motion Planning of Quadrotor Swarms in Cluttered Environments
arXiv
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arXiv 2023年
作者: Adajania, Vivek K. Zhou, Siqi Singh, Arun Kumar Schoellig, Angela P. Learning Systems and Robotics Lab Germany University of Toronto Institute for Aerospace Studies Canada Technical University of Munich Germany Vector Institute for Artificial Intelligence Canada University of Tartu Estonia
This paper presents a scalable online algorithm to generate safe and kinematically feasible trajectories for quadrotor swarms. Existing approaches rely on linearizing Euclidean distance-based collision constraints and... 详细信息
来源: 评论