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Automatic generation of modules of object categorization for autonomous mobile robots

AIP Conference Proceedings 2013年第1期1558卷

作者： Anna Gorbenko Ural Federal University Department of Intelligent Systems and Robotics Mathematics and Computer Science Institute Lenin st. 51 620083 Ekaterinburg Russia

Many robotic tasks require advanced systems of visual sensing. Robotic systems of visual sensing must be able to solve a number of different complex problems of visual data analysis. Object categorization is one of such problems. In this paper, we propose an approach to automatic generation of computationally effective modules of object categorization for autonomous mobile robots. This approach is based on the consideration of the stack cover problem. In particular, it is assumed that the robot is able to perform an initial inspection of the environment. After such inspection, the robot needs to solve the stack cover problem by using a supercomputer. A solution of the stack cover problem allows the robot to obtain a template for computationally effective scheduling of object categorization. Also, we consider an efficient approach to solve the stack cover problem. In particular, we consider an explicit reduction from the decision version of the stack cover problem to the satisfiability problem. For different satisfiability algorithms, the results of computational experiments are presented.

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Syntactic algorithm of two-dimensional scene analysis for unmanned flying vehicles

Syntactic algorithm of two-dimensional scene analysis for un...

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International Conference on computer Vision and Graphics, ICCVG 2012

作者： Bielecki, Andrzej Buratowski, Tomasz Śmigielski, Piotr Institute of Computer Science Faculty of Mathematics and Computer Science Jagiellonian University Lojasiewicza 6 30-348 Kraków Poland Department of Robotics and Mechatronics Faculty of Mechanical Engineering and Robotics AGH University of Science and Technology Al. Mickiewicza 30 30-059 Kraków Poland Asseco Poland S.A. Podwale 3 31-118 Kraków Poland

ISBN: (纸本)9783642335631

In this paper the approach to on-line object recognition for autonomous flying agent is considered. The method is divided into two parts. First the algorithm for scene objects vectorization is introduced. As the second step of the overall method we present the rotation and scale invariant algorithm for vectorized object identification based on syntactic language. © 2012 Springer-Verlag Berlin Heidelberg.

关键词： Autonomous agents

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The hamiltonian alternating path problem

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IAENG International Journal of Applied mathematics 2012年第4期42卷 204-213页

作者： Gorbenko, Anna Popov, Vladimir Ural Federal University Department of Intelligent Systems and Robotics of Mathematics Computer Science Institute 620083 Ekaterinburg Russia

In this paper, we consider the Hamiltonian alternating path problem for graphs, multigraphs, and digraphs. We describe an approach to solve the problem. This approach is based on constructing logical models for the problem. We use logical models for the Hamiltonian alternating path problem to solve the Hamiltonian path problem and the planning a typical working day for indoor service robots problem. Also, we use these models for Bennett's model of cytogenetics, automatic generation of recognition modules, and algebraic data.

关键词： Hamiltonians

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The c-fragment longest arc-preserving common subsequence problem

IAENG International Journal of Computer Science

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IAENG International Journal of computer science 2012年第3期39卷 231-238页

作者： Gorbenko, Anna Popov, Vladimir Ural Federal University Department of Intelligent Systems Robotics of Mathematics and Computer Science Institute 620083 Ekaterinburg Russia

Arc-annotated sequences are useful in representing the structural information of RNA and protein sequences. In particular, arc-annotated sequences are useful in describing the secondary and tertiary structures of RNA and protein sequences. Structure comparison for RNA and for protein sequences has become a central computational problem bearing many challenging computer science questions. The longest arc-preserving common subsequence problem has been introduced as a framework for studying the similarity of arc-annotated sequences. It is a sound and meaningful mathematical formalization of comparing the secondary structures of molecular sequences. In this paper, we consider two special cases of the longest arc-preserving common subsequence problem, efragment LAPCS (unlimited, plain), c-fragment LAPCS (unlimited, unlimited). In particular, we consider a parameterized version of the 1-fragment LAPCS (unlimited, plain) problem, parameterized by the length l of the desired subsequence. We show W[1]-completeness of the problem. Also, we describe an approach to solve c-fragment LAPCS (unlimited, unlimited). This approach is based on constructing logical models for the problem.

关键词： RNA

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A novel swarm intelligence algorithm and its application in solving wireless sensor networks coverage problems

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Journal of Networks 2012年第12期7卷 2037-2043页

作者： Mo, Yuanbin Liu, Jizhong Wang, Baolei Jonathan Wu, Q.M. College of Mathematics and Computer Science Guangxi University for Nationalities Nanning 530006 China School of Mechanical and Electrical Engineering Institute of Robotics of Nanchang University Nanchang University Nanchang 330031 China Department of Electrical and Computer Engineering Computer Vision and Sensing Systems Laboratory University of Windsor Windsor N9B3P4 Canada

Wireless sensor networks (WSNs) have attracted a great deal of research due to their wide-range of potential applications. Sensor deployment and coverage problems are their important issues. This article briefly introduces the principle of swarm intelligence (SI). A novel SI algorithm based on information sharing of Particle Swarm Optimization (PSO) and diversity maintenance mechanism of Artificial Immune System (AIS) is designed and the model of coverage problems is given. Its applications in solving different deterministic and random coverage problems are given. The algorithm used in obtaining maximum coverage probability with given number of sensor nodes and minimum number of sensor nodes with required coverage probability of WSNs deterministic coverage, and determining the selected sensor nodes with coverage probability and connectivity requirement of WSNs random coverage, are analyzed in detail. The simulation results show the algorithm is practical. The applications of SI on K- coverage and connectivity problems in the future are also projected in the article. © 2012 ACADEMY PUBLISHER.

关键词： Swarm intelligence

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Dynamic model of a hyper-redundant, octopus-like manipulator for underwater applications

Dynamic model of a hyper-redundant, octopus-like manipulator...

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2011 IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Rongjie Kang Asimina Kazakidi Emanuele Guglielmino David T. Branson Dimitris P. Tsakiris John A. Ekaterinaris Darwin G. Caldwell Department of Advanced Robotics Istituto Italiano di Tecnologia Genova Italy Institute of Computer Science Foundation for Research and Technology Hellas FORTH Heraklion Greece Institute of Applied and Computational Mathematics Foundation for Research and Technology Hellas FORTH Heraklion Greece

The octopus arm is a unique tool that combines strength and flexibility. It can shorten, elongate and bend at any point along its length. To model this behavior, a hyper-redundant manipulator composed of multiple segments is proposed. Each segment is a parallel robotic mechanism with redundant actuation. The kinematics and dynamics of this manipulator are analyzed and simulated utilizing a modular computational modeling method. Simulation results for some primitive movements are presented, and the effect of hydrodynamic forces is included.

关键词： Mathematical model Force Manipulator dynamics Joints Equations Pistons

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Reports of the AAAI 2010 fall symposia

Reports of the AAAI 2010 fall symposia

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作者： Azevedo, Roger Biswas, Gautam Bohus, Dan Carmichael, Ted Finlayson, Mark A. Hadzikadic, Mirsad Havasi, Catherine Horvitz, Eric Kanda, Takayuki Koyejo, Oluwasanmi Lawless, William F. Lenat, Doug Meneguzzi, Felipe Mutlu, Bilge Oh, Jean Pirrone, Roberto Raux, Antoine Sofge, Donald A. Sukthankar, Gita Van Durme, Benjamin Yorke-Smith, Neil Department of Educational and Counseling Psychology McGill University Canada Center for Intelligent Systems Vanderbilt University United States Microsoft Research Redmond United States Department of Software and Information Systems University of North Carolina Charlotte United States Complex Systems Institute United States Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology United States Media Lab. Massachusetts Institute of Technology United States ATR Intelligent Robotics and Communication Laboratories Kyoto Japan Department of Electrical and Computer Engineering University of Texas Austin United States Department of Mathematics Paine College Augusta GA United States Cycorp Austin TX United States Robotics Institute Carnegie Mellon University United States Department of Computer Sciences University of Wisconsin Madison United States University of Palermo Italy Honda Research Institute United States Navy Center for Applied Research in Artificial Intelligence Naval Research Laboratory Washington DC United States Department of Electrical Engineering and Computer Science University of Central Florida United States Department of Computer Science Johns Hopkins University United States American University of Beirut Lebanon SRI International's Artificial Intelligence Center United States

The Association for the Advancement of Artificial Intelligence (AAAI) presented the 2010 Fall Symposium Series on November 11-13, 2010. The eight symposia included Cognitive and Metacognitive Educational Systems, Commonsense Knowledge, Complex Adaptive Systems: Resilience, Robustness, and Evolvability, Computational Models of Narrative, Dialog with Robots, Manifold Learning and Its Applications, Proactive Assistant Agents and Quantum Informatics for Cognitive, Social, and Semantic Processes. Cognitive and Metacognitive Educational Systems aimed to provide a comprehensive definition of metacognitive educational systems that is inclusive of the theoretical, architectural, and educational aspects of this field. The AAAI Commonsense Knowledge Fall Symposium had the goal of bringing together the diverse elements of this community whose work benefits from or contributes to the representation of general knowledge about the world. One of the specific goals of Proactive symposium was to gather the researchers from various projects in assistant agents to share their wisdom in retrospect.

关键词： Semantics

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Path recognition for outdoor navigation using artificial neural networks: Case study

Path recognition for outdoor navigation using artificial neu...

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IEEE-ICIT 2010 International Conference on Industrial Technology, ICIT 2010

作者： Shinzato, Patrick Y. Fernandes, Leandro C. Osorio, Fernando S. Wolf, Denis F. Mobile Robotics Laboratory Institute of Mathematics and Computer Science University of Sao Paulo Sao Carlos - SP Brazil

ISBN: (纸本)9781424456970

Navigation is a broad topic that has been receiving considerable attention from the mobile robotic community. In order to execute a safe navigation on outdoors it is necessary to identify parts of the terrain that can be traversed by the robot and parts that should be avoided. This paper describes an analyses of an image-based terrain identification based on different visual information using a multi-layer perceptron neural network. Experimental tests using an outdoor robot and a video camera have been conducted in real scenarios to evaluate the proposed methods. ©2010 IEEE.

关键词： Video cameras

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Learning the consequences of actions: Representing effects as feature changes

Learning the consequences of actions: Representing effects a...

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2010 International Conference on Emerging Security Technologies, EST 2010, Robots and Security, ROBOSEC 2010, Learning and Adaptive Behavior in Robotic Systems, LAB-RS 2010

作者： Rudolph, Mathias Mühlig, Manuel Gienger, Michael Böhme, Hans-Joachim Faculty of Mathematics and Computer Science University of Applied Sciences Dresden 01069 Dresden Germany Honda Research Institute Europe Carl-Legien-Strasse 30 63073 Offenbach/Main Germany Research Institute for Cognition and Robotics Bielefeld University 33594 Bielefeld Germany

ISBN: (纸本)9780769541754

In advanced Programming by Demonstration (PbD) it is important to give a robot the ability to understand the effects of an action. This ability can enable a robot to not only mimic an action but to imitate, by determining whether an action succeeded or not, or to emulate, by finding another action that causes the same effects as observed. In this paper we propose a system that uses a Bayesian Network structure to store actions as a representation of their effects. The effects in turn are implicitly stored as representation of feature changes in the perceived environment. In a more general form the system can be used to differentiate between actions. In a more specific form it can be used to learn complex mapping functions. We will show three different experiments. The first one shows how to learn actions as a representation of effects. The second one shows how our system can be used to learn a complex mapping function on robot movement and in the third experiment, we illustrate how to combine these independently learned systems to achieve more complex tasks. © 2010 IEEE.

关键词： Bayesian networks

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Learning the Consequences of Actions: Representing Effects as Feature Changes

Learning the Consequences of Actions: Representing Effects a...

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International Conference on Emerging Security Technologies (EST)

作者： Mathias Rudolph Manuel Mühlig Michael Gienger Hans-Joachim Böhme Faculty of Mathematics and Computer Science University of Applied Sciences Dresden Dresden Germany Honda Research Institute Europe Offenbach/Main Germany Research Institute of Cognition and Robotics Bielefeld University Bielefeld Germany

关键词： Robots Bayesian methods Probabilistic logic Accuracy Force Joints Planing

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