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检索条件"机构=Computational Learning and Motor Control"
70 条 记 录,以下是31-40 订阅
排序:
An MPC Walking Framework With External Contact Forces
An MPC Walking Framework With External Contact Forces
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IEEE International Conference on Robotics and Automation
作者: Sean Mason Nicholas Rotella Stefan Schaal Ludovic Righetti Computational Learning and Motor Control Lab University of Southern California Los Angeles California Tandon School of Engineering New York University New York USA
In this work, we present an extension to a linear Model Predictive control (MPC) scheme that plans external contact forces for the robot when given multiple contact locations and their corresponding friction cone. To ... 详细信息
来源: 评论
control of legged robots with optimal distribution of contact forces
Control of legged robots with optimal distribution of contac...
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2011 11th IEEE-RAS International Conference on Humanoid Robots, HUMANOIDS 2011
作者: Righetti, Ludovic Buchli, Jonas Mistry, Michael Schaal, Stefan Computational Learning and Motor Control Lab. University of Southern California Los Angeles CA 90089 United States Max Planck Institute for Intelligent Systems Tübingen Germany Dept. of Advanced Robotics Italian Institute of Technology Genoa Italy Disney Research Pittsburgh Pittsburgh PA 15213 United States
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
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On the design of LQR kernels for efficient controller learning
arXiv
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arXiv 2017年
作者: Marco, Alonso Hennig, Philipp Schaal, Stefan Trimpe, Sebastian Max Planck Institute for Intelligent Systems Tübingen72076 Germany Computational Learning and Motor Control Lab University of Southern California Los Angeles United States
Finding optimal feedback controllers for nonlinear dynamic systems from data is hard. Recently, Bayesian optimization (BO) has been proposed as a powerful framework for direct controller tuning from experimental trial... 详细信息
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Efficient Bayesian Local Model learning for control
Efficient Bayesian Local Model Learning for Control
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IEEE/RSJ International Conference on Intelligent Robots and Systems
作者: Franziska Meier Philipp Hennig Stefan Schaal Computational Learning and Motor Control Lab University of Southern California Los Angeles CA 90089 USA Max-Planck-Institute for Intelligent Systems 72076 Tubingen Germany
Model-based control is essential for compliant control and force control in many modern complex robots, like humanoid or disaster robots. Due to many unknown and hard to model nonlinearities, analytical models of such... 详细信息
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Inertial Sensor-Based Humanoid Joint State Estimation
Inertial Sensor-Based Humanoid Joint State Estimation
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IEEE International Conference on Robotics and Automation
作者: Nicholas Rotella Sean Mason Stefan Schaal Ludovic Righetti Computational Learning and Motor Control Lab University of Southern California Los Angeles California Autonomous Motion Department Max Planck Institute for Intelligent Systems Tuebingen Germany
This work presents methods for the determination of a humanoid robot's joint velocities and accelerations directly from link-mounted Inertial Measurement Units (IMUs) each containing a three-axis gyroscope and a t... 详细信息
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Balancing and walking using full dynamics LQR control with contact constraints
Balancing and walking using full dynamics LQR control with c...
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IEEE-RAS International Conference on Humanoid Robots
作者: Sean Mason Nicholas Rotella Stefan Schaal Ludovic Righetti Computational Learning and Motor Control Lab University of Southern California Los Angeles California Autonomous Motion Department Max Planck Institute for Intelligent Systems Tuebingen Germany
Torque control algorithms which consider robot dynamics and contact constraints are important for creating dynamic behaviors for humanoids. As computational power increases, algorithms tend to also increase in complex... 详细信息
来源: 评论
Full dynamics LQR control of a humanoid robot: An experimental study on balancing and squatting
Full dynamics LQR control of a humanoid robot: An experiment...
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IEEE-RAS International Conference on Humanoid Robots
作者: Sean Mason Ludovic Righetti Stefan Schaal Computational Learning and Motor Control Lab University of Southern California Los Anleles California Autonomous Motion Department Max Planck Institute for Intelligent Systems Tuebingen Germany
Humanoid robots operating in human environments require whole-body controllers that can offer precise tracking and well-defined disturbance rejection behavior. In this contribution, we propose an experimental evaluati... 详细信息
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Probabilistic Object Tracking using a Range Camera
Probabilistic Object Tracking using a Range Camera
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IEEE/RSJ International Conference on Intelligent Robots and Systems
作者: Manuel Wuthrich Peter Pastor Mrinal Kalakrishnan Jeannette Bohg Stefan Schaal Autonomous Motion Department at the Max-Planck-Institute for Intelligent Systems Tubingen Germany Computational Learning and Motor Control lab at the University of Southern California Los Angeles CA USA
We address the problem of tracking the 6-DoF pose of an object while it is being manipulated by a human or a robot. We use a dynamic Bayesian network to perform inference and compute a posterior distribution over the ... 详细信息
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learning and Adaptation of Inverse Dynamics Models: A Comparison
Learning and Adaptation of Inverse Dynamics Models: A Compar...
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IEEE-RAS International Conference on Humanoid Robots
作者: Kevin Hitzler Franziska Meier Stefan Schaal Tamim Asfour Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology Karlsruhe Germany Max-Planck-Institute of Intelligent Systems Germany and Computational Learning and Motor Control Lab University of Southern California USA
Performing tasks with high accuracy while interacting with the real world requires a robot to have an exact representation of its inverse dynamics that can be adapted to new situations. In the past, various methods fo... 详细信息
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Balancing and walking using full dynamics LQR control with contact constraints
arXiv
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arXiv 2017年
作者: Mason, Sean Rotella, Nicholas Schaal, Stefan Righetti, Ludovic Computational Learning and Motor Control Lab University of Southern California Los AngelesCA United States Autonomous Motion Department Max Planck Institute for Intelligent Systems Tuebingen Germany
Torque control algorithms which consider robot dynamics and contact constraints are important for creating dynamic behaviors for humanoids. As computational power increases, algorithms tend to also increase in complex... 详细信息
来源: 评论