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Learning task constraints for robot grasping using graphical models

Learning task constraints for robot grasping using graphical...

引用

23rd IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems, IROS 2010

作者： Song, D. Huebner, K. Kyrki, V. Kragic, D. KTH Royal Institute of Technology Stockholm Sweden Computer Vision and Active Perception Lab. Centre for Autonomous Systems Sweden Lappeenranta University of Technology Department of Information Technology Finland

ISBN: (纸本)9781424466757

This paper studies the learning of task constraints that allow grasp generation in a goal-directed manner. We show how an object representation and a grasp generated on it can be integrated with the task requirements. The scientific problems tackled are (i) identification and modeling of such task constraints, and (ii) integration between a semantically expressed goal of a task and quantitative constraint functions defined in the continuous object-action domains. We first define constraint functions given a set of object and action attributes, and then model the relationships between object, action, constraint features and the task using Bayesian networks. The probabilistic framework deals with uncertainty, combines apriori knowledge with observed data, and allows inference on target attributes given only partial observations. We present a system designed to structure data generation and constraint learning processes that is applicable to new tasks, embodiments and sensory data. The application of the task constraint model is demonstrated in a goal-directed imitation experiment. ©2010 IEEE.

关键词： Bayesian networks

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Interest point based tracking

Interest point based tracking

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2010 20th International Conference on Pattern Recognition, ICPR 2010

作者： Kloihofer, Werner Kampel, Martin Research and Development Image Processing Center Communication Systems GmbH Vienna Austria Computer Vision Lab. Vienna University of Technology Vienna Austria

ISBN: (纸本)9780769541099

This paper deals with a novel method for object tracking. In the first step interest points are detected and feature descriptors around them are calculated. Sets of known points are created, allowing tracking based on point matching. The set representation is updated online at every tracking step. Our method uses one-shot learning with the first frame, so no offline and no supervised learning is required. Following an object recognition based approach there is no need for a background model or motion model, allowing tracking of abrupt motion and with non-stationary cameras. We compare our method to MeanShift and Tracking via Online Boosting, showing the benefits of our approach. © 2010 IEEE.

关键词： Object detection

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A clustering algorithm use SOM and K-Means in Intrusion Detection

A clustering algorithm use SOM and K-Means in Intrusion Dete...

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International Conference on E-Business and E-Government (ICEE)

作者： Wang, Huai-Bin Yang, Hong-Liang Xu, Zhi-Jian Yuan, Zheng Tianjin Key Lab. of Intelligent Computing and Novel Software Technology Tianjin University of Technology 300191 Tianjin China Key Laboratory of Computer Vision and System Ministry of Education 300191 Tianjin China Key Laboratory of Computer Vision and System Ministry of Education China

ISBN: (纸本)9780769539973

Improving detection definition is a pivotal problem for intrusion detection. Many intelligent algorithms were used to improve the detection rate and reduce the false rate. Traditional SOM cannot provide the precise clustering results to us, while traditional K-Means depends on the initial value serious and it is difficult to find the center of cluster easily. Therefore, in this paper we introduce a new algorithm, first, we use SOM gained roughly clusters and center of clusters, then, using K-Means refine the clustering in the SOM stage. At last of this paper we take KDD CUP-99 dataset to test the performance of the new algorithm. The new algorithm overcomes the defects of traditional algorithms effectively. Experimental results show that the new algorithm has a good stability of efficiency and clustering accuracy. © 2010 IEEE.

关键词： Self organizing maps

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Compression of pre-computed per-pixel texture features using MDS

Compression of pre-computed per-pixel texture features using...

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作者： Pang, Wai-Man Wong, Hon-Cheng Spatial Media Group Computer Arts Lab. University of Aizu Aizu-Wakamatsu Japan Faculty of Information Technology Macau University of Science and Technology Macao China

ISBN: (纸本)9781424471348

There are many successful experiences employing texture analysis to improve the accuracy and robustness of image segmentation. Usually, per-pixel based texture analysis is required, which involves intensive computation especially for large images. Precomputation and storing of the texture features involves large file space which is not cost effective. To adopt to these novel needs, we propose the use of multidimensional scaling (MDS) technique to reduce the size of per-pixel texture features of an image while preserving the textural discrminiability for segmentation. Per-pixel texture features will create very large dissimilarity matrix, making the solving of MDS intractable. A sampling-based MDS is therefore introduced to tackle the problem with a divide-and-conquer approach. A compression ratio of 1:24 can be achieved with an average error rate lower than 7%. Preliminary experiments on segmentation using the compressed data show satisfactory results as good as using the uncompressed features. We foresee that such a method will allow texture features to be stored and transferred more efficiently on low processing power devices or embedded systems like mobile phones. © 2010 IEEE.

关键词： Pixels

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Probe-volume: An exploratory volume visualization framework

Probe-volume: An exploratory volume visualization framework

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2010 3rd International Congress on Image and Signal Processing, CISP 2010

作者： Ng, Ka-Wai Wong, Hon-Cheng Wong, Un-Hong Pang, Wai-Man Faculty of Information Technology Macau University of Science and Technology China Spatial Media Group Computer Arts Lab. University of Aizu Aizu-Wakamatsu City Japan

ISBN: (纸本)9781424465149

Direct volume rendering has been an important technique for visualizing volume data. An unobstructed view on the inspected features of interest can help the user to get the insight of the volume data being explored. In this paper an exploratory volume visualization framework named Probe-Volume is presented. Probe-Volume provides a moveable and sizeable probing box for the user to examine an interested volumetric space of the data enclosed by the box. High-quality volume rendered results with such a feature can be achieved efficiently by providing two different user specified transfer functions for regions inside and outside of the probing box. In addition, our framework allows the user to visualize the volume with four rendering modes, namely, Full, MIP, MIDA, and Contour. Combining with the probing box, the user can select different rendering effects for regions included and excluded by the box in order to improve the visual effects. Experimental results show that Probe-Volume can provide informative direct volume rendered images of raw volume data efficiently and effectively. ©2010 IEEE.

关键词： Probes

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Learning grasp stability based on tactile data and HMMs

Learning grasp stability based on tactile data and HMMs

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19th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2010

作者： Bekiroglu, Yasemin Kragic, Danica Kyrki, Ville Centre for Autonomous Systems and Computational Vision and Active Perception Lab. School of Computer Science and Communication KTH Stockholm Sweden Department of Information Technology Lappeenranta University of Technology Finland

ISBN: (纸本)9781424479917

In this paper, the problem of learning grasp stability in robotic object grasping based on tactile measurements is studied. Although grasp stability modeling and estimation has been studied for a long time, there are few robots today able of demonstrating extensive grasping skills. The main contribution of the work presented here is an investigation of probabilistic modeling for inferring grasp stability based on learning from examples. The main objective is classification of a grasp as stable or unstable before applying further actions on it, e.g. lifting. The problem cannot be solved by visual sensing which is typically used to execute an initial robot hand positioning with respect to the object. The output of the classification system can trigger a regrasping step if an unstable grasp is identified. An off-line learning process is implemented and used for reasoning about grasp stability for a three-fingered robotic hand using Hidden Markov models. To evaluate the proposed method, experiments are performed both in simulation and on a real robot system. © 2010 IEEE.

关键词： Hidden Markov models

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A new method of image data fusion based on FNN

A new method of image data fusion based on FNN

引用

2010 6th International Conference on Natural Computation, ICNC'10

作者： Zhang, De-Gan Li, Chao Wang, Dong Zhang, Xiao-Li Tianjin Key Lab. of Intelligent Computing and Novel Software Technology Tianjin University of Technology 300191 China Key Laboratory of Computer Vision and System Tianjin University of Technology Ministry of Education 300191 China

ISBN: (纸本)9781424459612

The image data are obtained by a variety of multimedia, information equipment, which include amount of information, extensive coverage, and redundancy in ubiquitous computing paradigm. In order to make use of these information reasonably and efficiently, it is necessary to fuse such massive data, therefore the multi-sensor image information fusion become a key technology to ubiquitous computing. A new approach of image data fusion based on fuzzy neural network (FNN) is presented in this paper. Here, neural network is a parallel information processing model, there are more adaptive and self-organization, and can accomplish the complexity of real-time computing and mass data retrieval, it demonstrate its unique superiority of image understanding, pattern recognition and the handling of incomplete information. In the new approach, fuzzy theory has the advantages such as: easy-to-understand, flexible and inclusive of non-precise data, as well as using expert knowledge and based on the natural language. The fuzzy neural network system developed by us has used in multi-sensor image fusion, proved that the fusion is fast, effective, good, and can meet the real-time requirements of ubiquitous computing. ©2010 IEEE.

关键词： Fuzzy neural networks

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Pano UMECHIKA: A crowded underground city panoramic view system

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作者： Arai, Ismail Hori, Maiya Kawai, Norihiko Abe, Yohei Ichikawa, Masahiro Satonaka, Yusuke Nitta, Tatsuki Nitta, Tomoyuki Fujii, Harumitsu Mukai, Masaki Horimi, Soichiro Makita, Koji Kanbara, Masayuki Nishio, Nobuhiko Yokoya, Naokazu Ubiquitous Computing and Networking Lab. Ritsumeikan University 1-1-1 Noji-Higashi Kusatsu Shiga 525-8577 Japan Vision and Media Computing Lab. Nara Institute of Science and Technology 8916-5 Takayama Ikoma Nara 630-0192 Japan

ISBN: (纸本)9783642148828

Toward a really useful navigation system, utilizing spherical panoramic photos with maps like Google Street View is efficient. Users expect the system to be availab.e in all areas they go. Conventional shooting methods obtain the shot position from GPS sensor. However, indoor areas are out of GPS range. Furthermore, most urban public indoor areas are crowded with pedestrians. Even if we blur the pedestrians in a photo, the photos with blurring are not useful for scenic information. Thus, we propose a method which simultaneously subtracts pedestrians based on background subtraction method and generates location metadata by manually input from maps. Using these methods, we achieved an underground panoramic view system which displays no pedestrians. © 2010 Springer-Verlag Berlin Heidelberg.

关键词： Global positioning system

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Boosted sigma set for pedestrian detection

Boosted sigma set for pedestrian detection

引用

International Conference on Pattern Recognition

作者： Hong, Xiaopeng Chang, Hong Chen, Xilin Gao, Wen School of Computer Science and Technology Harbin Institute of Technology China Key Lab. of Intelligent Information Processing Chinese Academy of Sciences Institute of Computing Technology China Institute of Digital Media Peking University China

ISBN: (纸本)9780769541099

This paper presents a new method to detect pedestrian in still image using Sigma sets as image region descriptors in the boosting framework. Sigma set encodes second order statistics of an image region implicitly in the form of a point set. Compared with the covariance matrix, the traditional second order statistics based region descriptor, which requires computationally demanding operations based on Riemannian manifold, Sigma set preserves similar robustness and discriminative power more efficiently because the classification on Sigma sets can be directly performed in vector space. Experimental results on the INRIA and the Daimler Chrysler pedestrian datasets show the effectiveness and efficiency of the proposed method. © 2010 IEEE.

关键词： Covariance matrix

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Zooming interfaces for augmented reality browsers

Zooming interfaces for augmented reality browsers

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12th International Conference on Human-computer Interaction with Mobile Devices and Services, Mobile HCI2010

作者： Alessandro, Mulloni Dünser, Andreas Schmalstieg, Dieter Institute for Computer Graphics and Vision Graz University of Technology Inffeldgasse 16 8010 Graz Austria HIT Lab. NZ University of Canterbury Private Bag 4800 Christchurch New Zealand

ISBN: (纸本)9781605588353

Augmented Reality combines real world and virtual information in interactive visualizations. Since phones started integrating GPS, compass and accelerometer, several Augmented Reality browsers for phones have hit the market. These are applications that access large amounts of geo-referenced information from online sources and present it at corresponding physical locations, superimposed onto a live video stream. However, Augmented Reality is constrained by the camera's field of view and restricted to first- person views, limiting the amount of overview that users can gain. We present two zooming interfaces that compensate for these constraints by enabling users to smoothly zoom between the Augmented Reality view and (1) an egocentric panoramic view of 360°, and (2) an exocentric top-down view. We present the results from two studies that show how in most search tasks our zooming interfaces are faster and require less panning than an overlay- based tool, scaling better as the amount of information grows. © 2010 ACM.

关键词： Augmented reality

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