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IOP Conference Series: Materials Science and Engineering 2019年第1期680卷

作者： M M Zhdanova V V Voronin R A Sizyakin M S Minkin A A Zelensky Lab. 'Mathematical methods of image processing and intelligent computer vision systems' Don State Technical University Gagarin sq. 1 Rostov-on-Don 344000 Russia Moscow State University of Technology 'STANKIN' Vadkovsky line 1 Moscow 127055 Russia

The tasks of recognition actions and classification objects are fundamental in computer vision systems. Even subtasks, such as recognition of atomic motion and single objects form the basis for understanding the situation in the work area and the scene in general. This is especially important in video surveillance systems designed to ensure security. Thus, the effectiveness of recognition and classification methods is one of the primary tasks of computer vision. But the visual methods implemented in similar video surveillance systems, encounter some difficulties, such as inhomogeneous background, uncontrolled operating environments, irregular illumination, etc. To address these drawbacks, the paper presents a model for combining visible range images and depth images. This model allows to improve the quality of recognized images, provides the construction of a more informative descriptor, which also positively affects the recognition efficiency. Our results show that it has good performance in fusion visible image and depth map.

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Integrating mission, logistics, and task planning for skills-based robot control in industrial kitting applications 34

Integrating mission, logistics, and task planning for skills...

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34th Workshop of the UK Planning and Scheduling Special Interest Group, PlanSIG 2016

作者： Crosby, Matthew Petrick, Ronald P. A. Toscano, César Dias, Rui Correia Rovida, Francesco Krüger, Volker Department of Computer Science Heriot-Watt University EdinburghEH14 4AS United Kingdom INESC TEC Technology and Science Porto4200 - 465 Portugal Robotics Vision and Machine Intelligence Lab. Aalborg University Copenhagen2450 Denmark

This paper presents an integrated cognitive robotics system for industrial kitting operations in a modern factory setting. The robot system combines low-level robot control and execution monitoring with automated mission and task planning, and a logistics planner which communicates with the factory's manufacturing execution system. The system has been implemented and tested on a series of automotive kitting problems, where collections of parts are picked from a warehouse and delivered to the production line. The system has been empirically evaluated and the complete framework shown to be successful at assembling kits in a small factory environment. © 2017, CEUR-WS. All rights reserved.

关键词： Robot programming

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A formal approach to anomaly detection 5

A formal approach to anomaly detection

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5th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2016

作者： Eriksson, André Kjellström, Hedvig Computer Vision and Active Perception Lab. KTH Royal Institute of Technology Stockholm Sweden

ISBN: (纸本)9789897581731

While many advances towards effective anomaly detection techniques targeting specific applications have been made in recent years, little work has been done to develop application-agnostic approaches to the subject. In this article, we present such an approach, in which anomaly detection methods are treated as formal, structured objects. We consider a general class of methods, with an emphasis on methods that utilize structural properties of the data they operate on. For this class of methods, we develop a decomposition into sub-methods-simple, restricted objects, which may be reasoned about independently and combined to form methods. As we show, this formalism enables the construction of software that facilitates formulating, implementing, evaluating, as well as algorithmically finding and calibrating anomaly detection methods. © Copyright 2016 by SCITEPRESS-Science and technology Publications, Lda. All rights reserved.

关键词： Formal methods

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WISERNet: Wider Separate-then-reunion Network for Steganalysis of Color Images

arXiv

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arXiv 2018年

作者： Zeng, Jishen Tan, Shunquan Liu, Guangqing Li, Bin Huang, Jiwu Guangdong Key Laboratory of Intelligent Information Processing National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen518060 China College of Computer Science and Software Engineering Shenzhen University Guangdong Key Lab. of Intelligent Info. Processing and Shenzhen Key Laboratory of Media Security Shenzhen University Shenzhen518060 China Peng Cheng Laboratory Shenzhen518052 China

Until recently, deep steganalyzers in spatial domain have been all designed for gray-scale images. In this paper, we propose WISERNet (the wider separate-then-reunion network) for steganalysis of color images. We provide theoretical rationale to claim that the summation in normal convolution is one sort of "linear collusion attack" which reserves strong correlated patterns while impairs uncorrelated noises. Therefore in the bottom convolutional layer which aims at suppressing correlated image contents, we adopt separate channel-wise convolution without summation instead. Conversely, in the upper convolutional layers we believe that the summation in normal convolution is beneficial. Therefore we adopt united normal convolution in those layers and make them remarkably wider to reinforce the effect of "linear collusion attack". As a result, our proposed wide-and-shallow, separate-then-reunion network structure is specifically suitable for color image steganalysis. We have conducted extensive experiments on color image datasets generated from BOSSBase raw images and another large-scale dataset which contains 100,000 raw images, with di_erent demosaicking algorithms and downsampling algorithms. The experimental results show that our proposed network outperforms other state-of-the-art color image steganalytic models either hand-crafted or learned using deep networks in the literature by a clear margin. Specifically, it is noted that the detection performance gain is achieved with less than half the complexity compared to the most advanced deeplearning steganalyzer as far as we know, which is scarce in the literature. Copyright © 2018, The Authors. All rights reserved.

关键词： Steganography

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RCAMP: A resilient communication-aware motion planner for mobile robots with autonomous repair of wireless connectivity

arXiv

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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 availab.e 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

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How behavior trees generalize the Teleo-Reactive paradigm and and-or-trees

How behavior trees generalize the Teleo-Reactive paradigm an...

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2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2016

作者： Colledanchise, Michele Ögren, Petter Computer Vision and Active Perception Lab. Centre for Autonomous Systems School of Computer Science and Communication KTH - Royal Institute of Technology StockholmSE-100 44 Sweden

ISBN: (纸本)9781509037629

Behavior Trees (BTs) is a way of organizing the switching structure of a control system, that was originally developed in the computer gaming industry but is now also being used in robotics. The Teleo-Reactive programs (TRs) is a highly cited reactive hierarchical robot control approach suggested by Nilsson and And-Or-Trees are trees used for heuristic problems solving. In this paper, we show that BTs generalize TRs as well as And-Or-Trees, even though the two concepts are quite different. And-Or-Trees are trees of conditions, and we show that they transform into a feedback execution plan when written as a BT. TRs are hierarchical control structures, and we show how every TR can be written as a BT. Furthermore, we show that so-called Universal TRs, guaranteeing that the goal will be reached, are a special case of so-called Finite Time Successful BTs. This implies that many designs and theoretical results developed for TRs can be applied to BTs. © 2016 IEEE.

关键词： Forestry

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Human and smart machine co-learning with brain computer interface

arXiv

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arXiv 2018年

作者： Lee, Chang-Shing Wang, Mei-Hui Ko, Li-Wei Prof, Naoyuki Kubota Lin, Lu-An Kitaoka, Shinya Wang, Yu-Te Su, Shun-Feng Computer Science and Information Engineering National Cheng Kung University Tainan Taiwan Taiwan National Chiao Tung University Hsinchu Taiwan Institute of Bioinformatics and Systems Biology National Chiao Tung University Taiwan Nagoya University Nagoya Japan Department of System Design Tokyo Metropolitan University Tokyo Japan OASE Lab. NUTN Taiwan Dwango Media Village DWANGO Co. Ltd. Japan La Jolla Swartz Center for Computational Neuroscience UCSD United States Purdue University West LafayetteIN United States Department of Electrical Engineering National Taiwan University of Science and Technology Taiwan

Machine learning has become a very popular approach for cybernetics systems, and it has always been considered important research in the Computational Intelligence area. Nevertheless, when it comes to smart machines, it is not just about the methodologies. We need to consider systems and cybernetics as well as include human in the loop. The purpose of this article is as follows: (1) To integrate the open source Facebook AI Research (FAIR) DarkForest program of Facebook with Item Response Theory (IRT), to the new open learning system, namely, DDF learning system;(2) To integrate DDF Go with Robot namely Robotic DDF Go system;(3) To invite the professional Go players to attend the activity to play Go games on site with a smart machine. The research team will apply this technology to education, such as, playing games to enhance the children concentration on learning mathematics, languages, and other topics. With the detected brainwaves, the robot will be able to speak some words that are very much to the point for the students and to assist the teachers in classroom in the future. Copyright © 2018, The Authors. All rights reserved.

关键词： Social networking (online)

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Adaptive control for pivoting with visual and tactile feedback

Adaptive control for pivoting with visual and tactile feedba...

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2016 IEEE International Conference on Robotics and Automation, ICRA 2016

作者： Vina, Francisco E.B. Karayiannidis, Yiannis Smith, Christian Kragic, Danica Computer Vision and Active Perception Lab. Centre for Autonomous Systems School of Computer Science and Communication Royal Institute of Technology KTH StockholmSE-100 44 Sweden Dept. of Signals and Systems Chalmers University of Technology GothenburgSE-412 96 Sweden

ISBN: (纸本)9781467380263

In this work we present an adaptive control approach for pivoting, which is an in-hand manipulation maneuver that consists of rotating a grasped object to a desired orientation relative to the robot's hand. We perform pivoting by means of gravity, allowing the object to rotate between the fingers of a one degree of freedom gripper and controlling the gripping force to ensure that the object follows a reference trajectory and arrives at the desired angular position. We use a visual pose estimation system to track the pose of the object and force measurements from tactile sensors to control the gripping force. The adaptive controller employs an update law that accommodates for errors in the friction coefficient, which is one of the most common sources of uncertainty in manipulation. Our experiments confirm that the proposed adaptive controller successfully pivots a grasped object in the presence of uncertainty in the object's friction parameters. © 2016 IEEE.

关键词： Friction

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How Behavior Trees generalize the Teleo-Reactive paradigm and And-Or-Trees

How Behavior Trees generalize the Teleo-Reactive paradigm an...

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2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Michele Colledanchise Petter Ögren Computer Vision and Active Perception Lab. KTH - Royal Institute of Technology Stockhalm Sweden

关键词： Service robots Batteries Control systems Industries Problem-solving computers

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Active perception and modeling of deformable surfaces using Gaussian processes and position-based dynamics

Active perception and modeling of deformable surfaces using ...

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IEEE-RAS International Conference on Humanoid Robots

作者： Sergio Caccamo Püren Güler Hedvig Kjellström Danica Kragic Computer Vision and Active Perception Lab. Royal Institute of Technology (KTH) Stockholm Sweden

ISBN: (纸本)9781509047192

Exploring and modeling heterogeneous elastic surfaces requires multiple interactions with the environment and a complex selection of physical material parameters. The most common approaches model deformable properties from sets of offline observations using computationally expensive force-based simulators. In this work we present an online probabilistic framework for autonomous estimation of a deformability distribution map of heterogeneous elastic surfaces from few physical interactions. The method takes advantage of Gaussian Processes for constructing a model of the environment geometry surrounding a robot. A fast Position-based Dynamics simulator uses focused environmental observations in order to model the elastic behavior of portions of the environment. Gaussian Process Regression maps the local deformability on the whole environment in order to generate a deformability distribution map. We show experimental results using a PrimeSense camera, a Kinova Jaco2 robotic arm and an Optoforce sensor on different deformable surfaces.

关键词： Shape Deformable models Gaussian processes Robot sensing systems Ground penetrating radar Surface treatment Computational modeling

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