检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

20 篇 会议
8 篇 期刊文献

馆藏范围

28 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

16 篇 工学
- 9 篇 机械工程
- 7 篇 仪器科学与技术
- 7 篇 控制科学与工程
- 4 篇 计算机科学与技术...
- 3 篇 力学（可授工学、理...
- 3 篇 软件工程
- 2 篇 电气工程
- 1 篇 生物工程
9 篇 理学
- 5 篇 数学
- 3 篇 物理学
- 3 篇 统计学（可授理学、...
- 1 篇 生物学
- 1 篇 系统科学
1 篇 法学
- 1 篇 社会学
1 篇 医学
- 1 篇 临床医学

主题

4 篇 humanoid robots
4 篇 trajectory
3 篇 robots
3 篇 robot kinematics
2 篇 three-dimensiona...
2 篇 couplings
2 篇 computational mo...
2 篇 entropy
2 篇 approximation me...
2 篇 estimation
2 篇 kinematics
2 篇 dynamics
2 篇 data models
2 篇 joints
2 篇 heuristic algori...
1 篇 pd control
1 篇 tuning
1 篇 legged locomotio...
1 篇 model predictive...
1 篇 center of mass

机构

7 篇 autonomous motio...
5 篇 bosch center for...
5 篇 computational le...
4 篇 computational le...
3 篇 computational le...
2 篇 computational le...
2 篇 engineering depa...
2 篇 computational le...
2 篇 lincoln center f...
2 篇 autonomous motio...
2 篇 computational le...
2 篇 autonomous motio...
2 篇 autonomous motio...
2 篇 extreme robotics...
2 篇 university of tü...
1 篇 institute of inf...
1 篇 preventive medic...
1 篇 department of ph...
1 篇 research center ...
1 篇 tandon school of...

作者

13 篇 stefan schaal
6 篇 schaal stefan
5 篇 ludovic righetti
5 篇 jeannette bohg
4 篇 nicholas rotella
4 篇 gerhard neumann
3 篇 righetti ludovic
3 篇 rotella nicholas
3 篇 daniel kappler
3 篇 sean mason
2 篇 mason sean
2 篇 doerr andreas
2 篇 becker philipp
2 篇 nguyen-tuong duy
2 篇 marco alonso
2 篇 alexander herzog
2 篇 taylor james
2 篇 neumann gerhard
2 篇 trimpe sebastian
2 篇 zhao cheng

语言

27 篇 英文
1 篇 中文

检索条件"机构=Computational Learning for Autonomous Systems"

共 28 条记录，以下是1-10 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

Optimal control and inverse optimal control by distribution matching

Optimal control and inverse optimal control by distribution ...

引用

IEEE/RSJ International Conference on Intelligent Robots and systems

作者： Oleg Arenz Hany Abdulsamad Gerhard Neumann Computational Learning for Autonomous Systems TU Darmstadt 64287 Germany Intelligent Autonomous Systems TU Darmstadt 64287 Germany

ISBN: (纸本)9781509037636

Optimal control is a powerful approach to achieve optimal behavior. However, it typically requires a manual specification of a cost function which often contains several objectives, such as reaching goal positions at different time steps or energy efficiency. Manually trading-off these objectives is often difficult and requires a high engineering effort. In this paper, we present a new approach to specify optimal behavior. We directly specify the desired behavior by a distribution over future states or features of the states. For example, the experimenter could choose to reach certain mean positions with given accuracy/variance at specified time steps. Our approach also unifies optimal control and inverse optimal control in one framework. Given a desired state distribution, we estimate a cost function such that the optimal controller matches the desired distribution. If the desired distribution is estimated from expert demonstrations, our approach performs inverse optimal control. We evaluate our approach on several optimal and inverse optimal control tasks on non-linear systems using incremental linearizations similar to differential dynamic programming approaches.

关键词： Optimal control Entropy Heuristic algorithms Trajectory Cost function learning (artificial intelligence)

来源：评论

学校读者我要写书评

暂无评论

Robust policy updates for stochastic optimal control

Robust policy updates for stochastic optimal control

引用

IEEE-RAS International Conference on Humanoid Robots

作者： Elmar Rueckert Max Mindt Jan Peters Gerhard Neumann Intelligent Autonomous Systems Lab Technische Universitat Darmstadt Darmstadt Germany Robot Learning Group Max-Planck Institute for Intelligent Systems Tuebingen Germany Computational Learning for Autonomous Systems Darmstadt Germany

For controlling high-dimensional robots, most stochastic optimal control algorithms use approximations of the system dynamics and of the cost function (e.g., using linearizations and Taylor expansions). These approximations are typically only locally correct, which might cause instabilities in the greedy policy updates, lead to oscillations or the algorithms diverge. To overcome these drawbacks, we add a regularization term to the cost function that punishes large policy update steps in the trajectory optimization procedure. We applied this concept to the Approximate Inference Control method (AICO), where the resulting algorithm guarantees convergence for uninformative initial solutions without complex hand-tuning of learning rates. We evaluated our new algorithm on two simulated robotic platforms. A robot arm with five joints was used for reaching multiple targets while keeping the roll angle constant. On the humanoid robot Nao, we show how complex skills like reaching and balancing can be inferred from desired center of gravity or end effector coordinates.

关键词： Approximation algorithms Robot kinematics Trajectory Planning Approximation methods Gravity

来源：评论

学校读者我要写书评

暂无评论

Compact models of motor primitive variations for predictable reaching and obstacle avoidance

Compact models of motor primitive variations for predictable...

引用

9th IEEE-RAS International Conference on Humanoid Robots, HUMANOIDS09

作者： Stulp, Freek Oztop, Erhan Pastor, Peter Beetz, Michael Schaaz, Stefan Computational Learning and Motor Control Lab. University of Southern California Los Angeles CA United States Kyoto Japan Computational Neuroscience Laboratories Advanced Telecommunications Research Institute International Kyoto Japan Intelligent Autonomous Systems Group Technische Universitdt Munchen Munich Germany

ISBN: (纸本)9781424445882

In most activities of daily living, related tasks are encountered over and over again. This regularity allows humans and robots to reuse existing solutions for known recurring tasks. We expect that reusing a set of standard solutions to solve similar tasks will facilitate the design and on-line adaptation of the control systems of robots operating in human environments. In this paper, we derive a set of standard solutions for reaching behavior from human motion data. We also derive stereotypical reaching trajectories for variations of the task, in which obstacles are present. These stereotypical trajectories are then compactly represented with Dynamic Movement Primitives. On the humanoid robot Sarcos CB, this approach leads to reproducible, predictable, and human-like reaching motions. ©2009 IEEE.

关键词： Anthropomorphic robots

来源：评论

学校读者我要写书评

暂无评论

Recurrent Kaiman networks: Factorized inference in high-dimensional deep feature spaces 36

Recurrent Kaiman networks: Factorized inference in high-dime...

引用

36th International Conference on Machine learning, ICML 2019

作者： Becker, Philipp Pandya, Harit Gebhardt, Gregor Zhao, Cheng Taylor, James Neumann, Gerhard Computational Learning for Autonomous Systems TU Darmstadt Darmstadt Germany Bosch Center for Artificial Intelligence Renningen Germany University of Tübingen Tübingen Germany Lincoln Center for Autonomous Systems University of Lincoln Lincoln United Kingdom Extreme Robotics Lab University of Birmingham Birmingham United Kingdom Engineering Department Lancaster University Lancaster United Kingdom

ISBN: (纸本)9781510886988

In order to integrate uncertainty estimates into deep time-series modelling, Kaiman Filters (KFs) (Kaiman et al., 1960) have been integrated with deep learning models, however, such approaches typically rely on approximate inference techniques such as variational inference which makes learning more complex and often less scalable due to approximation errors. We propose a new deep approach to Kaiman filtering which can be learned directly in an end-to-end manner using backpropagation without additional approximations. Our approach uses a high-dimensional factorized latent state representation for which the Kaiman updates simplify to scalar operations and thus avoids hard to backpropagate, computationally heavy and potentially unstable matrix inversions. Moreover, we use locally linear dynamic models to efficiently propagate the latent state to the next time step. The resulting network architecture, which we call Recurrent Kaiman Network (RKN), can be used for any time-series data, similar to a LSTM (Hochreiter & Schmidhuber, 1997) but uses an explicit representation of uncertainty. As shown by our experiments, the RKN obtains much more accurate uncertainty estimates than an LSTM or Gated Recurrent Units (GRUs) (Cho et al., 2014) while also showing a slightly improved prediction performance and outperforms various recent generative models on an image imputation task. © 36th International Conference on Machine learning, ICML 2019. All rights reserved.

关键词： Network architecture

来源：评论

学校读者我要写书评

暂无评论

Model-based policy search for automatic tuning of multivariate PID controllers

Model-based policy search for automatic tuning of multivaria...

引用

2017 IEEE International Conference on Robotics and Automation, ICRA 2017

作者： Doerr, Andreas Nguyen-Tuong, Duy Marco, Alonso Schaal, Stefan Trimpe, Sebastian Bosch Center for Artificial Intelligence Renningen Germany Autonomous Motion Department Max Planck Institute for Intelligent Systems Tübingen Germany Computational Learning and Motor Control Lab University of Southern California Los AngelesCA United States

ISBN: (纸本)9781509046331

PID control architectures are widely used in industrial applications. Despite their low number of open parameters, tuning multiple, coupled PID controllers can become tedious in practice. In this paper, we extend PILCO, a model-based policy search framework, to automatically tune multivariate PID controllers purely based on data observed on an otherwise unknown system. The system's state is extended appropriately to frame the PID policy as a static state feedback policy. This renders PID tuning possible as the solution of a finite horizon optimal control problem without further a priori knowledge. The framework is applied to the task of balancing an inverted pendulum on a seven degree-of-freedom robotic arm, thereby demonstrating its capabilities of fast and data-efficient policy learning, even on complex real world problems. © 2017 IEEE.

关键词： Inverted pendulum

来源：评论

学校读者我要写书评

暂无评论

State Estimation for a Humanoid Robot

State Estimation for a Humanoid Robot

引用

IEEE/RSJ International Conference on Intelligent Robots and systems

作者： Nicholas Rotella Michael Bloesch Ludovic Righetti Stefan Schaal Computational Learning and Motor Control Lab University of Southern California Los Angeles California Autonomous Systems Lab ETH Zurich Zurich Switzerland Autonomous Motion Department Max Planck Institute for Intelligent Systems Tuebingen Germany

ISBN: (纸本)9781479969357

This paper introduces a framework for state estimation on a humanoid robot platform using only common proprioceptive sensors and knowledge of leg kinematics. The presented approach extends that detailed in prior work on a point-foot quadruped platform by adding the rotational constraints imposed by the humanoid's flat feet. As in previous work, the proposed Extended Kalman Filter accommodates contact switching and makes no assumptions about gait or terrain, making it applicable on any humanoid platform for use in any task. A nonlinear observability analysis is performed on both the point-foot and flat-foot filters and it is concluded that the addition of rotational constraints significantly simplifies singular cases and improves the observability characteristics of the system. Results on a simulated walking dataset demonstrate the performance gain of the flat-foot filter as well as confirm the results of the presented observability analysis.

关键词： Humanoid robots State estimation Observability Platform Flatfoot

来源：评论

学校读者我要写书评

暂无评论

Robot arm pose estimation through pixel-wise part classification

Robot arm pose estimation through pixel-wise part classifica...

引用

IEEE International Conference on Robotics and Automation (ICRA)

作者： Jeannette Bohg Javier Romero Alexander Herzog Stefan Schaal Autonomous Motion Department Perceiving Systems Max-Planck-Institute for Intelligent Systems Tübingen Germany Computational Learning and Motor Control lab University of Southern California Los Angeles CA USA

We propose to frame the problem of marker-less robot arm pose estimation as a pixel-wise part classification problem. As input, we use a depth image in which each pixel is classified to be either from a particular robot part or the background. The classifier is a random decision forest trained on a large number of synthetically generated and labeled depth images. From all the training samples ending up at a leaf node, a set of offsets is learned that votes for relative joint positions. Pooling these votes over all foreground pixels and subsequent clustering gives us an estimate of the true joint positions. Due to the intrinsic parallelism of pixel-wise classification, this approach can run in super real-time and is more efficient than previous ICP-like methods. We quantitatively evaluate the accuracy of this approach on synthetic data. We also demonstrate that the method produces accurate joint estimates on real data despite being purely trained on synthetic data.

关键词： Joints Three-dimensional displays Robot sensing systems Estimation Training data Kinematics

来源：评论

学校读者我要写书评

暂无评论

Balancing and walking using full dynamics LQR control with contact constraints

Balancing and walking using full dynamics LQR control with c...

引用

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

ISBN: (纸本)9781509047192

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 complexity. However, it is not clear how much complexity is really required to create controllers which exhibit good performance. In this paper, we study the capabilities of a simple approach based on contact consistent LQR controllers designed around key poses to control various tasks on a humanoid robot. We present extensive experimental results on a hydraulic, torque controlled humanoid performing balancing and stepping tasks. This feedback control approach captures the necessary synergies between the DoFs of the robot to guarantee good control performance. We show that for the considered tasks, it is only necessary to re-linearize the dynamics of the robot at different contact configurations and that increasing the number of LQR controllers along desired trajectories does not improve performance. Our result suggest that very simple controllers can yield good performance competitive with current state of the art, but more complex, optimization-based whole-body controllers. A video of the experiments can be found at https://***/5T08CNKV1hw.

关键词： Legged locomotion Dynamics Trajectory Robot kinematics Couplings Humanoid robots

来源：评论

学校读者我要写书评

暂无评论

Inertial Sensor-Based Humanoid Joint State Estimation

Inertial Sensor-Based Humanoid Joint State Estimation

引用

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

ISBN: (纸本)9781467380270

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 three-axis accelerometer. No information about the global pose of the floating base or its links is required and precise knowledge of the link IMU poses is not necessary due to presented calibration routines. Additionally, a filter is introduced to fuse gyroscope angular velocities with joint position measurements and compensate the computed joint velocities for time-varying gyroscope biases. The resulting joint velocities are subject to less noise and delay than filtered velocities computed from numerical differentiation of joint potentiometer signals, leading to superior performance in joint feedback control as demonstrated in experiments performed on a SARCOS hydraulic humanoid.

关键词： demonstrated experiments performed SARCOS

来源：评论

学校读者我要写书评

暂无评论

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...

引用

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 evaluation of a linear quadratic regulator (LQR) using a linearization of the full robot dynamics together with the contact constraints. The advantage of the controller is that it explicitly takes into account the coupling between the different joints to create optimal feedback controllers for whole-body control. We also propose a method to explicitly regulate other tasks of interest, such as the regulation of the center of mass of the robot or its angular momentum. In order to evaluate the performance of linear optimal control designs in a real-world scenario (model uncertainty, sensor noise, imperfect state estimation, etc), we test the controllers in a variety of tracking and balancing experiments on a torque controlled humanoid (e.g. balancing, split plane balancing, squatting, pushes while squatting, and balancing on a wheeled platform). The proposed control framework shows a reliable push recovery behavior competitive with more sophisticated balance controllers, rejecting impulses up to 11.7 Ns with peak forces of 650 N, with the added advantage of great computational simplicity. Furthermore, the controller is able to track squatting trajectories up to 1 Hz without relinearization, suggesting that the linearized dynamics is sufficient for significant ranges of motion.

关键词： Joints Humanoid robots Iron Dynamics Aerospace electronics Couplings

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共3页 << < 1 2 3 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：