检索结果-内蒙古大学图书馆

arXiv 2017年

作者： Caccamo, Sergio Parasuraman, Ramviyas Freda, Luigi Gianni, Mario Ögren, Petter Computer Vision and Active Perception Lab. Centre for Autonomous Systems School of Computer Science and Communication KTH Royal Institute of Technology Sweden Purdue University West Lafayette United States ALCOR Laboratory DIAG Sapienza University of Rome Italy

Mobile robots, be it autonomous or teleoperated, require stable communication with the base station to exchange valuable information. Given the stochastic elements in radio signal propagation, such as shadowing and fading, and the possibilities of unpredictable events or hardware failures, communication loss often presents a significant mission risk, both in terms of probability and impact, especially in Urban Search and Rescue (USAR) operations. Depending on the circumstances, disconnected robots are either abandoned, or attempt to autonomously back-trace their way to the base station. Although recent results in Communication-Aware Motion Planning can be used to effectively manage connectivity with robots, there are no results focusing on autonomously re-establishing the wireless connectivity of a mobile robot without back-tracing or using detailed a priori information of the network. In this paper, we present a robust and online radio signal mapping method using Gaussian Random Fields, and propose a Resilient Communication-Aware Motion Planner (RCAMP) that integrates the above signal mapping framework with a motion planner. RCAMP considers both the environment and the physical constraints of the robot, based on the available sensory information. We also propose a self-repair strategy using RCMAP, that takes both connectivity and the goal position into account when driving to a connection-safe position in the event of a communication loss. We demonstrate the proposed planner in a set of realistic simulations of an exploration task in single or multi-channel communication scenarios. Copyright © 2017, The Authors. All rights reserved.

关键词： Mobile robots

来源：评论

学校读者我要写书评

暂无评论

Model-aided State Estimation for Quadrotor Micro Air Vehicles amidst Wind Disturbances

Model-aided State Estimation for Quadrotor Micro Air Vehicle...

引用

IEEE/RSJ International Conference on Intelligent Robots and systems

作者： Dinuka Abeywardena Zhan Wang Gamini Dissanayake Steven L. Waslander Sarath Kodagoda Centre for Autonomous Systems University of Technology Sydney Computer Vision and Active Perception Lab Centre for Autonomous Systems CSC The Royal Institute of Technology KTH Stockholm 100 44 Sweden Waterloo Autonomous Vehicles Laboratory University of Waterloo Waterloo ON Canada N2L 3G1

ISBN: (纸本)9781479969357

This paper extends the recently developed Model-Aided Visual-Inertial Fusion (MA-VIF) technique for quadrotor Micro Air Vehicles (MAV) to deal with wind disturbances. The wind effects are explicitly modelled in the quadrotor dynamic equations excluding the unobservable wind velocity component. This is achieved by a nonlinear observability of the dynamic system with wind effects. We show that using the developed model, the vehicle pose and two components of the wind velocity vector can be simultaneously estimated with a monocular camera and an inertial measurement unit. We also show that the MA-VIF is reasonably tolerant to wind disturbances, even without explicit modelling of wind effects and explain the reasons for this behaviour. Experimental results using a Vicon motion capture system are presented to demonstrate the effectiveness of the proposed method and validate our claims.

关键词： Mathematical model Wind speed Equations Observability Accelerometers Vectors Vehicle dynamics

来源：评论

学校读者我要写书评

暂无评论

A probabilistic framework for task-oriented grasp stability assessment

A probabilistic framework for task-oriented grasp stability ...

引用

IEEE International Conference on Robotics and Automation (ICRA)

作者： Yasemin Bekiroglu Dan Song Lu Wang Danica Kragic Centre for Autonomous Systems and the Computer Vision and Active Perception Laboratory CSC Royal Institute of Technology Stockholm Sweden

ISBN: (纸本)9781467356404

We present a probabilistic framework for grasp modeling and stability assessment. The framework facilitates assessment of grasp success in a goal-oriented way, taking into account both geometric constraints for task affordances and stability requirements specific for a task. We integrate high-level task information introduced by a teacher in a supervised setting with low-level stability requirements acquired through a robot's self-exploration. The conditional relations between tasks and multiple sensory streams (vision, proprioception and tactile) are modeled using Bayesian networks. The generative modeling approach both allows prediction of grasp success, and provides insights into dependencies between variables and features relevant for object grasping.

关键词： Robot sensing systems Bayes methods Stability analysis Probabilistic logic Planning Grasping

来源：评论

学校读者我要写书评

暂无评论

Learning a dictionary of prototypical grasp-predicting parts from grasping experience

Learning a dictionary of prototypical grasp-predicting parts...

引用

IEEE International Conference on Robotics and Automation (ICRA)

作者： Renaud Detry Carl Henrik Ek Marianna Madry Danica Kragic Centre for Autonomous Systems and the Computer Vision and Active Perception Laboratory CSC Royal Institute of Technology Stockholm Sweden

We present a real-world robotic agent that is capable of transferring grasping strategies across objects that share similar parts. The agent transfers grasps across objects by identifying, from examples provided by a teacher, parts by which objects are often grasped in a similar fashion. It then uses these parts to identify grasping points onto novel objects. We focus our report on the definition of a similarity measure that reflects whether the shapes of two parts resemble each other, and whether their associated grasps are applied near one another. We present an experiment in which our agent extracts five prototypical parts from thirty-two real-world grasp examples, and we demonstrate the applicability of the prototypical parts for grasping novel objects.

关键词： Robots Shape Prototypes Three-dimensional displays Grasping Dictionaries Training

来源：评论

学校读者我要写书评

暂无评论

Sparse summarization of robotic grasping data

Sparse summarization of robotic grasping data

引用

IEEE International Conference on Robotics and Automation (ICRA)

作者： Martin Hjelm Carl Henrik Ek Renaud Detry Hedvig Kjellström Danica Kragic Centre for Autonomous Systems Computer Vision and Active Perception Laboratory CSC Royal Institute of Technology Stockholm Sweden

ISBN: (纸本)9781467356404

We propose a new approach for learning a summarized representation of high dimensional continuous data. Our technique consists of a Bayesian non-parametric model capable of encoding high-dimensional data from complex distributions using a sparse summarization. Specifically, the method marries techniques from probabilistic dimensionality reduction and clustering. We apply the model to learn efficient representations of grasping data for two robotic scenarios.

关键词： Robots Data models Grasping Shape Kernel Optimization Encoding

来源：评论

学校读者我要写书评

暂无评论

Model-free robot manipulation of doors and drawers by means of fixed-grasps

Model-free robot manipulation of doors and drawers by means ...

引用

IEEE International Conference on Robotics and Automation (ICRA)

作者： Yiannis Karayiannidis Christian Smith Francisco E. Viña Petter Ögren Danica Kragic Computer Vision and Active Perception Laboratory Centre for Autonomous Systems School of Computer Science and Communication Royal Institute of Technology Stockholm Sweden

This paper addresses the problem of robot interaction with objects attached to the environment through joints such as doors or drawers. We propose a methodology that requires no prior knowledge of the objects' kinematics, including the type of joint - either prismatic or revolute. The method consists of a velocity controller which relies on force/torque measurements and estimation of the motion direction, rotational axis and the distance from the center of rotation. The method is suitable for any velocity controlled manipulator with a force/torque sensor at the end-effector. The force/torque control regulates the applied forces and torques within given constraints, while the velocity controller ensures that the end-effector moves with a task-related desired tangential velocity. The paper also provides a proof that the estimates converge to the actual values. The method is evaluated in different scenarios typically met in a household environment.

关键词： Torque Force Robots Hardware

来源：评论

学校读者我要写书评

暂无评论

Grasping objects with holes: A topological approach

Grasping objects with holes: A topological approach

引用

IEEE International Conference on Robotics and Automation (ICRA)

作者： Florian T. Pokorny Johannes A. Stork Danica Kragic Computer Vision and Active Perception Laboratory Centre for Autonomous Systems School of Computer Science and Communication Royal Institute of Technology Stockholm Sweden

ISBN: (纸本)9781467356404

This work proposes a topologically inspired approach for generating robot grasps on objects with `holes'. Starting from a noisy point-cloud, we generate a simplicial representation of an object of interest and use a recently developed method for approximating shortest homology generators to identify graspable loops. To control the movement of the robot hand, a topologically motivated coordinate system is used in order to wrap the hand around such loops. Finally, another concept from topology - namely the Gauss linking integral - is adapted to serve as evidence for secure caging grasps after a grasp has been executed. We evaluate our approach in simulation on a Barrett hand using several target objects of different sizes and shapes and present an initial experiment with real sensor data.

关键词： Noise measurement Robots Jacobian matrices

来源：评论

学校读者我要写书评

暂无评论

Predicting human intention in visual observations of hand/object interactions

Predicting human intention in visual observations of hand/ob...

引用

IEEE International Conference on Robotics and Automation (ICRA)

作者： Dan Song Nikolaos Kyriazis Iason Oikonomidis Chavdar Papazov Antonis Argyros Darius Burschka Danica Kragic Computer Vision & Active Perception Laboratory Centre for Autonomous Systems Royal Institute of Technology Stockholm Sweden Institute of Computer Science Foundation for Research and Technology-Hellas Crete Greece Technische Universität München Munich Germany

ISBN: (纸本)9781467356404

The main contribution of this paper is a probabilistic method for predicting human manipulation intention from image sequences of human-object interaction. Predicting intention amounts to inferring the imminent manipulation task when human hand is observed to have stably grasped the object. Inference is performed by means of a probabilistic graphical model that encodes object grasping tasks over the 3D state of the observed scene. The 3D state is extracted from RGB-D image sequences by a novel vision-based, markerless hand-object 3D tracking framework. To deal with the high-dimensional state-space and mixed data types (discrete and continuous) involved in grasping tasks, we introduce a generative vector quantization method using mixture models and self-organizing maps. This yields a compact model for encoding of grasping actions, able of handling uncertain and partial sensory data. Experimentation showed that the model trained on simulated data can provide a potent basis for accurate goal-inference with partial and noisy observations of actual real-world demonstrations. We also show a grasp selection process, guided by the inferred human intention, to illustrate the use of the system for goal-directed grasp imitation.

关键词： Grasping Three-dimensional displays Data models Robot sensing systems Bayes methods computational modeling

来源：评论

学校读者我要写书评

暂无评论

Improving generalization for 3D object categorization with Global Structure Histograms

Improving generalization for 3D object categorization with G...

引用

2012 IEEE/RSJ International Conference on Intelligent Robots and systems

作者： Marianna Madry Carl Henrik Ek Renaud Detry Kaiyu Hang Danica Kragic Centre for Autonomous Systems and the Computer Vision and Active Perception Laboratory CSC KTH Royal Institute of Technology Stockholm Sweden

ISBN: (纸本)9781467317375

We propose a new object descriptor for three dimensional data named the Global Structure Histogram (GSH). The GSH encodes the structure of a local feature response on a coarse global scale, providing a beneficial trade-off between generalization and discrimination. Encoding the structural characteristics of an object allows us to retain low local variations while keeping the benefit of global representativeness. In an extensive experimental evaluation, we applied the framework to category-based object classification in realistic scenarios. We show results obtained by combining the GSH with several different local shape representations, and we demonstrate significant improvements to other state-of-the-art global descriptors.

关键词： Histograms Robustness Encoding Databases Image color analysis Shape Data models

来源：评论

学校读者我要写书评

暂无评论

Object recognition using saliency maps and HTM learning

Object recognition using saliency maps and HTM learning

引用

2012 IEEE International Conference on Imaging systems and Techniques, IST 2012

作者： Kostavelis, Ioannis Nalpantidis, Lazaros Gasteratos, Antonios Laboratory of Robotics and Automation Department of Production and Management Engineering Democritus University of Thrace Vas. Sofias 12 GR-67100 Xanthi Greece Computer Vision and Active Perception Lab. Centre for Autonomous Systems Royal Institute of Technology - KTH SE-100 44 Stockholm Sweden

ISBN: (纸本)9781457717741

In this paper a pattern classification and object recognition approach based on bio-inspired techniques is presented. It exploits the Hierarchical Temporal Memory (HTM) topology, which imitates human neocortex for recognition and categorization tasks. The HTM comprises a hierarchical tree structure that exploits enhanced spatiotemporal modules to memorize objects appearing in various orientations. In accordance with HTM's biological inspiration, human vision mechanisms can be used to preprocess the input images. Therefore, the input images undergo a saliency computation step, revealing the plausible information of the scene, where a human might fixate. The adoption of the saliency detection module releases the HTM network from memorizing redundant information and augments the classification accuracy. The efficiency of the proposed framework has been experimentally evaluated in the ETH-80 dataset, and the classification accuracy has been found to be greater than other HTM systems. © 2012 IEEE.

关键词： Object recognition

来源：评论

学校读者我要写书评

暂无评论

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：

请选择收藏分类：

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

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：