Sonar

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Sonar (originally an acronym for SOund Navigation And Ranging) is a technique that uses sound propagation (usually underwater, as in Submarine navigation) to navigate, communicate with or detect other vessels. (Wikipedia.org)






Conferences related to Sonar

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Oceans 2020 MTS/IEEE GULF COAST

To promote awareness, understanding, advancement and application of ocean engineering and marine technology. This includes all aspects of science, engineering, and technology that address research, development, and operations pertaining to all bodies of water. This includes the creation of new capabilities and technologies from concept design through prototypes, testing, and operational systems to sense, explore, understand, develop, use, and responsibly manage natural resources.

  • OCEANS 2018 MTS/IEEE Charleston

    Ocean, coastal, and atmospheric science and technology advances and applications

  • OCEANS 2017 - Anchorage

    Papers on ocean technology, exhibits from ocean equipment and service suppliers, student posters and student poster competition, tutorials on ocean technology, workshops and town meetings on policy and governmental process.

  • OCEANS 2016

    The Marine Technology Scociety and the Oceanic Engineering Society of the IEEE cosponor a joint annual conference and exposition on ocean science, engineering, and policy. The OCEANS conference covers four days. One day for tutorials and three for approx. 500 technical papers and 150 -200 exhibits.

  • OCEANS 2015

    The Marine Technology Scociety and the Oceanic Engineering Society of the IEEE cosponor a joint annual conference and exposition on ocean science, engineering, and policy. The OCEANS conference covers four days. One day for tutorials and three for approx. 450 technical papers and 150-200 exhibits.

  • OCEANS 2014

    The OCEANS conference covers four days. One day for tutorials and three for approx. 450 technical papers and 150-200 exhibits.

  • OCEANS 2013

    Three days of 8-10 tracks of technical sessions (400-450 papers) and concurent exhibition (150-250 exhibitors)

  • OCEANS 2012

    Ocean related technology. Tutorials and three days of technical sessions and exhibits. 8-12 parallel technical tracks.

  • OCEANS 2011

    The Marine Technology Society and the Oceanic Engineering Scociety of the IEEE cosponsor a joint annual conference and exposition on ocean science engineering, and policy.

  • OCEANS 2010

    The Marine Technology Society and the Oceanic Engineering Scociety of the IEEE cosponsor a joint annual conference and exposition on ocean science engineering, and policy.

  • OCEANS 2009

  • OCEANS 2008

    The Marine Technology Society (MTS) and the Oceanic Engineering Society (OES) of the Institute of Electrical and Electronic Engineers (IEEE) cosponsor a joint conference and exposition on ocean science, engineering, education, and policy. Held annually in the fall, it has become a focal point for the ocean and marine community to meet, learn, and exhibit products and services. The conference includes technical sessions, workshops, student poster sessions, job fairs, tutorials and a large exhibit.

  • OCEANS 2007

  • OCEANS 2006

  • OCEANS 2005

  • OCEANS 2004

  • OCEANS 2003

  • OCEANS 2002

  • OCEANS 2001

  • OCEANS 2000

  • OCEANS '99

  • OCEANS '98

  • OCEANS '97

  • OCEANS '96


2019 21st European Conference on Power Electronics and Applications (EPE '19 ECCE Europe)

Energy conversion and conditioning technologies, power electronics, adjustable speed drives and their applications, power electronics for smarter grid, energy efficiency,technologies for sustainable energy systems, converters and power supplies


2019 IEEE International Conference on Industrial Technology (ICIT)

The scope of the conference will cover, but will not be limited to, the following topics: Robotics; Mechatronics; Industrial Automation; Autonomous Systems; Sensing and artificial perception, Actuators and Micro-nanotechnology; Signal/Image Processing and Computational Intelligence; Control Systems; Electronic System on Chip and Embedded Control; Electric Transportation; Power Electronics; Electric Machines and Drives; Renewable Energy and Smart Grid; Data and Software Engineering, Communication; Networking and Industrial Informatics.


2019 IEEE International Ultrasonics Symposium (IUS)

The conference covers all aspects of the technology associated with ultrasound generation and detection and their applications.


2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

CVPR is the premier annual computer vision event comprising the main conference and severalco-located workshops and short courses. With its high quality and low cost, it provides anexceptional value for students, academics and industry researchers.

  • 2020 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premier annual computer vision event comprising the main conference and several co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry researchers.

  • 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premier annual computer vision event comprising the main conference and several co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry researchers.

  • 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conferenceand 27co-located workshops and short courses. With its high quality and low cost, it provides anexceptional value for students,academics and industry.

  • 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry.

  • 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    computer, vision, pattern, cvpr, machine, learning

  • 2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. Main conference plus 50 workshop only attendees and approximately 50 exhibitors and volunteers.

  • 2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry.

  • 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Topics of interest include all aspects of computer vision and pattern recognition including motion and tracking,stereo, object recognition, object detection, color detection plus many more

  • 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Sensors Early and Biologically-Biologically-inspired Vision, Color and Texture, Segmentation and Grouping, Computational Photography and Video

  • 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Concerned with all aspects of computer vision and pattern recognition. Issues of interest include pattern, analysis, image, and video libraries, vision and graphics, motion analysis and physics-based vision.

  • 2009 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Concerned with all aspects of computer vision and pattern recognition. Issues of interest include pattern, analysis, image, and video libraries, vision and graphics,motion analysis and physics-based vision.

  • 2008 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2007 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2006 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2005 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)


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Periodicals related to Sonar

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Aerospace and Electronic Systems Magazine, IEEE

The IEEE Aerospace and Electronic Systems Magazine publishes articles concerned with the various aspects of systems for space, air, ocean, or ground environments.


Antennas and Propagation, IEEE Transactions on

Experimental and theoretical advances in antennas including design and development, and in the propagation of electromagnetic waves including scattering, diffraction and interaction with continuous media; and applications pertinent to antennas and propagation, such as remote sensing, applied optics, and millimeter and submillimeter wave techniques.


Automatic Control, IEEE Transactions on

The theory, design and application of Control Systems. It shall encompass components, and the integration of these components, as are necessary for the construction of such systems. The word `systems' as used herein shall be interpreted to include physical, biological, organizational and other entities and combinations thereof, which can be represented through a mathematical symbolism. The Field of Interest: shall ...


Computer Graphics and Applications, IEEE

IEEE Computer Graphics and Applications (CG&A) bridges the theory and practice of computer graphics. From specific algorithms to full system implementations, CG&A offers a strong combination of peer-reviewed feature articles and refereed departments, including news and product announcements. Special Applications sidebars relate research stories to commercial development. Cover stories focus on creative applications of the technology by an artist or ...


Electron Devices, IEEE Transactions on

Publishes original and significant contributions relating to the theory, design, performance and reliability of electron devices, including optoelectronics devices, nanoscale devices, solid-state devices, integrated electronic devices, energy sources, power devices, displays, sensors, electro-mechanical devices, quantum devices and electron tubes.


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Most published Xplore authors for Sonar

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Xplore Articles related to Sonar

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Active sonar reverberation suppression based on beam space data normalization

[{u'author_order': 1, u'affiliation': u'National Key Laboratory of Science and Technology on Sonar, Hangzhou Applied Acoustics Research Institute, Hangzhou, China', u'full_name': u'Jun Wang'}, {u'author_order': 2, u'affiliation': u'National Key Laboratory of Science and Technology on Sonar, Hangzhou Applied Acoustics Research Institute, Hangzhou, China', u'full_name': u'Chao Wang'}, {u'author_order': 3, u'affiliation': u'National Key Laboratory of Science and Technology on Sonar, Hangzhou Applied Acoustics Research Institute, Hangzhou, China', u'full_name': u'Tao Cheng'}] 2017 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC), 2017

Reverberation is the main interference in active sonar detection, due to its special properties, reverberation suppression is a difficult problem in active sonar signal processing. In this paper, the method of reverberation suppression is studied, and a new method based on the normalization of the beam space data is proposed. The basic idea of this method is to normalize the ...


IEE Colloquium on 'Simulation Techniques Applied to Sonar' (Digest No.80)

[] IEE Colloquium on Simulation Techniques Applied to Sonar, 1988

None


The reverberation suppression in wideband diver detection sonar

[{u'author_order': 1, u'affiliation': u'Image Sonar Technology Lab, Institute of Acoustics, Chinese Academy of Sciences, Beijing, China', u'authorUrl': u'https://ieeexplore.ieee.org/author/37571127700', u'full_name': u'Yang Juan', u'id': 37571127700}, {u'author_order': 2, u'affiliation': u'Image Sonar Technology Lab, Institute of Acoustics, Chinese Academy of Sciences, Beijing, China', u'authorUrl': u'https://ieeexplore.ieee.org/author/37577307600', u'full_name': u'Xu Feng', u'id': 37577307600}, {u'author_order': 3, u'affiliation': u'Image Sonar Technology Lab, Institute of Acoustics, Chinese Academy of Sciences, Beijing, China', u'authorUrl': u'https://ieeexplore.ieee.org/author/37085377810', u'full_name': u'Liu Jia', u'id': 37085377810}, {u'author_order': 4, u'affiliation': u'Image Sonar Technology Lab, Institute of Acoustics, Chinese Academy of Sciences, Beijing, China', u'authorUrl': u'https://ieeexplore.ieee.org/author/37085376226', u'full_name': u'An Xudong', u'id': 37085376226}, {u'author_order': 5, u'affiliation': u'Image Sonar Technology Lab, Institute of Acoustics, Chinese Academy of Sciences, Beijing, China', u'authorUrl': u'https://ieeexplore.ieee.org/author/37085529236', u'full_name': u'Ji Yongqiang', u'id': 37085529236}] 2014 Oceans - St. John's, 2014

The reverberation suppression is the foundation of target detection in diver detection sonar. The reverberation caused by the sea bottom is generally strong. Conventional methods with only amplitude cannot remove these reverberations completely because of the random temporal fluctuation of the signal amplitude, which causes false alarms especially in the small target detection. Spatiotemporal stability derived from the variance of ...


A detection method based on sonar image for underwater pipeline tracker

[{u'author_order': 1, u'affiliation': u'Department of Precision Mechanical Engineering, Shanghai University, China', u'authorUrl': u'https://ieeexplore.ieee.org/author/37835880900', u'full_name': u'Jinbo Chen', u'id': 37835880900}, {u'author_order': 2, u'affiliation': u'Department of Precision Mechanical Engineering, Shanghai University, China', u'authorUrl': u'https://ieeexplore.ieee.org/author/37283171700', u'full_name': u'Zhenbang Gong', u'id': 37283171700}, {u'author_order': 3, u'affiliation': u'Department of Precision Mechanical Engineering, Shanghai University, China', u'authorUrl': u'https://ieeexplore.ieee.org/author/37900501300', u'full_name': u'Hengyu Li', u'id': 37900501300}, {u'author_order': 4, u'affiliation': u'Department of Precision Mechanical Engineering, Shanghai University, China', u'authorUrl': u'https://ieeexplore.ieee.org/author/37291180000', u'full_name': u'Shaorong Xie', u'id': 37291180000}] 2011 Second International Conference on Mechanic Automation and Control Engineering, 2011

The surveillance and inspection of underwater pipelines are carried out by operators who drive a remotely operated underwater vehicle (ROV) with camera mounted on it. However in very turbid water, the camera can not capture any scene, even with auxiliary high-intensity light. In this case the optical detection devices are unable to complete the surveillance task In recent years, forward ...


Real-time SAS processing for high-arctic AUV surveys

[{u'author_order': 1, u'affiliation': u'Kraken Sonar Systems, 113 Terminal Road, Conception Bay South, NL, A1X 7B5, Canada', u'authorUrl': u'https://ieeexplore.ieee.org/author/37085403372', u'full_name': u'David Shea', u'id': 37085403372}, {u'author_order': 2, u'affiliation': u'Kraken Sonar Systems, 113 Terminal Road, Conception Bay South, NL, A1X 7B5, Canada', u'authorUrl': u'https://ieeexplore.ieee.org/author/37085423689', u'full_name': u'David Dawe', u'id': 37085423689}, {u'author_order': 3, u'affiliation': u'Kraken Sonar Systems, 113 Terminal Road, Conception Bay South, NL, A1X 7B5, Canada', u'authorUrl': u'https://ieeexplore.ieee.org/author/37271101800', u'full_name': u'Jeremy Dillon', u'id': 37271101800}, {u'author_order': 4, u'affiliation': u'Kraken Sonar Systems, 113 Terminal Road, Conception Bay South, NL, A1X 7B5, Canada', u'authorUrl': u'https://ieeexplore.ieee.org/author/37431198800', u'full_name': u'Sean Chapman', u'id': 37431198800}] 2014 IEEE/OES Autonomous Underwater Vehicles (AUV), 2014

Interferometrie Synthetic Aperture Sonar (InSAS) delivers ultra-high range independent image resolution with 3D seabed bathymetry at higher Area Coverage Rates (ACRs) and resolution than can be achieved with traditional physical aperture limited sidescan sonar. The along track resolution is achieved by synthesising the required aperture length by moving a physical aperture while sampling the field of view. The result is ...


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Educational Resources on Sonar

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eLearning

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IEEE-USA E-Books

  • From Bat Pinnae to Sonar Antennae: Augmented Obliquely Truncated Horns as a Novel Parametric Shape Model

    Biosonar systems operating in air (bats) use intricate baffle shapes for shaping the sonar beam pattern. Because of its relative ease of implementation, beamforming with such baffle shapes is also an attractive solution for enhancing the sonar-sensing capabilities of animats. The work presented here introduces a novel family of parametric, biologically inspired, baffle-shapes for sonar sensors: augmented obliquely truncated horns. The structural features of these shapes are: an obliquely truncated horn, a washboard ripple pattern on its inner surface, and a pin-shaped flap (“tragus”) partially occluding the aperture through which sound enters the baffle. Shapes generated by this model can be completely controlled with 22 parameters. Numerical methods to generate representations of these shapes, evaluate their acoustic properties, and visualize the results are described. The investigated acoustical system properties are: directivity pattern, shape of iso-gain surfaces in three dimensions and gain contours on planar cuts through the spatial distribution of the gain. The last property (cuts) serves as a representation of the shape of a sonar spotlight shone onto an extended target of relatively low curvature. The results demonstrate that ripple and tragus have a profound impact on the functional properties of the baffle shapes. The most prominent effects include breaking of symmetry and generation of side lobes in different frequency bands. The two features have been shown offer the opportunity to shape the spatial distribution of receiver gain into a large number of profoundly different configurations. Evidence of interactions between the features indicates that a combination of both features may generate system properties inaccessible through any one feature alone. The tool-chain of numerical methods used in the present work establishes a foundation for future investigations of performance measures to be used in optimizing the baffle shapes for a particular task.

  • Biomimetic Sonar Processing: From Dolphin Echolocation to Artificial Neural Networks

    Analysis of animal performance can provide important cues about the design of automated artificial biomimetic systems. On the basis of behavioral observations, we have been developing models of dolphin echolocation ability that have applicability to the design of biomimetic sonar systems. A dolphin was trained to perform an echolocation delayed matching-to-sample task. The clicks the animal generated during task performance were recorded and digitized along with the echoes returned by the stimulus objects. The dolphin's performance was then modeled using artifical neural networks.

  • Applications to Mobile Communications and Radar/Sonar

    In Chapter 7, applications in mobile communications and radar/sonar systems are presented. A model for the wireless channel is developed. It is shown how, in the case of relative motion between transmitter and receiver or between radar and target, the almost-cyclostationary transmitted signal is modified into a received signal with a different kind of nonstationarity. Conditions under which the generalized almost-cyclostationary or spectrally correlated model are appropriate for the received signal are derived.

  • OFDM Modem Development

    This chapter describes the modem implementation aspect and presents some example designs of orthogonal frequency‐division multiplexing (OFDM) based acoustic modems. To have a standalone underwater acoustic modem, which supports point to point communications, the following components are needed: hardware platform consisting of various units and DSP firmware. Demonstration of acoustic communication algorithms can be accomplished with low cost in the air, which often serves the educational purposes. The underwater sensor network (UWSN) lab at University of Connecticut has developed an OFDM lab modem prototype based on a DSP development board, as discussed in the chapter. AquaSeNT, a startup from the University of Connecticut, has licensed the OFDM modem technologies from the University of Connecticut and has launched a commercial modem product, which is also discussed in the chapter.

  • Towards a theory of how bats navigate through foliage

    In this paper we study echolocation by spectral analysis as a possible mechanism used by bats to navigate through their natural environment. We simulate the echo signals received by a bat inspired sonar system confronted with realistic reflectors, i.e. a large number of closely spaced scatterers. We propose a method to localize such natural reflectors on the basis of the time-frequency representation of the returned echo that is calculated by the bat's cochlea. The sonar system is simplified into a piston emitter and two piston receivers, of which the latter can be rotated. The method proposed reconstructs the environment by comparing the returned echoes with predefined templates corresponding with echoes from different angles. We show that the overlap between members of this set of templates can be used as a measure of their accuracy for localization purposes. This method is then applied to both monaural and binaural sonar systems and is shown to allow useful navigation behaviour. The problem of ghost images, i.e. erroneous interpretations of ambiguous position estimates, is shown to be inherent to single measurement based decisions. Finally, we show how active control of the ear configuration allows binaural sonar systems to eliminate ghost images by combining the resuits from a sequence of measurements, each corresponding with a well chosen ear configuration. Despite the description in this paper being restricted to the two-dimensional situation, this is not essential and we discuss how the mechanism described can be straightforwardly extended to the full 3D case.

  • Visual Looming as a range sensor for mobile robots

    This paper describes and evaluates visual looming as a method for monocular range estimation. The looming algorithm is based on the relationship between displacements of the observer relative to an object, and the resulting change in the size of the object's image on the focal plane of the camera. Though the looming algorithm has been described in detail in prior reports, its usefulness for inexpensive, robust ranging has not been realized widely. In this paper we analyze visual looming as a visual range sensor for autonomous mobile robots. Systematic experiments with a Pioneer i mobile robot show that visual looming can be used to extract ranging information much as with sonar. The accuracy of the looming algorithm is found to be significantly more robust than sonar when the object whose distance is being measured is slanted relative to the robot's line of sight. On the other hand, sonar is better suited for objects that cannot be visually segmented from their background, or objects that do not fit entirely within the focal plane. The results suggest that looming can be used as a robust, inexpensive range sensor as a complement to sonar.

  • Advanced Radar Detection Schemes Under Mismatched Signal Models

    Adaptive detection of signals embedded in correlated Gaussian noise has been an active field of research in the last decades. This topic is important in many areas of signal processing such as, just to give some examples, radar, sonar, communications, and hyperspectral imaging. Most of the existing adaptive algorithms have been designed following the lead of the derivation of Kelly's detector which assumes perfect knowledge of the target steering vector. However, in realistic scenarios, mismatches are likely to occur due to both environmental and instrumental factors. When a mismatched signal is present in the data under test, conventional algorithms may suffer severe performance degradation. The presence of strong interferers in the cell under test makes the detection task even more challenging. An effective way to cope with this scenario relies on the use of "tunable" detectors, i.e., detectors capable of changing their directivity through the tuning of proper parameters. The aim of this book is to present some recent advances in the design of tunable detectors and the focus is on the so-called two-stage detectors, i.e., adaptive algorithms obtained cascading two detectors with opposite behaviors. We derive exact closed-form expressions for the resulting probability of false alarm and the probability of detection for both matched and mismatched signals embedded in homogeneous Gaussian noise. It turns out that such solutions guarantee a wide operational range in terms of tunability while retaining, at the same time, an overall performance in presence of matched signals commensurate with Kelly's detector. Table of Contents: Introduction / Adaptive Radar Detection of Targets / Adaptive Detection Schemes for Mismatched Signals / Enhanced Adaptive Sidelobe Blanking Algorithms / Conclusions

  • Advances in Waveform-Agile Sensing for Tracking

    Recent advances in sensor technology and information processing afford a new flexibility in the design of waveforms for agile sensing. Sensors are now developed with the ability to dynamically choose their transmit or receive waveforms in order to optimize an objective cost function. This has exposed a new paradigm of significant performance improvements in active sensing: dynamic waveform adaptation to environment conditions, target structures, or information features. The manuscript provides a review of recent advances in waveform-agile sensing for target tracking applications. A dynamic waveform selection and configuration scheme is developed for two active sensors that track one or multiple mobile targets. A detailed description of two sequential Monte Carlo algorithms for agile tracking are presented, together with relevant Matlab code and simulation studies, to demonstrate the benefits of dynamic waveform adaptation. The work will be of interest not only to practitioners of radar and sonar, but also other applications where waveforms can be dynamically designed, such as communications and biosensing. Table of Contents: Waveform-Agile Target Tracking Application Formulation / Dynamic Waveform Selection with Application to Narrowband and Wideband Environments / Dynamic Waveform Selection for Tracking in Clutter / Conclusions / CRLB Evaluation for Gaussian Envelope GFM Chirp from the Ambiguity Function / CRLB Evaluation from the Complex Envelope

  • Spectral Analysis of Signals: The Missing Data Case

    Spectral estimation is important in many fields including astronomy, meteorology, seismology, communications, economics, speech analysis, medical imaging, radar, sonar, and underwater acoustics. Most existing spectral estimation algorithms are devised for uniformly sampled complete-data sequences. However, the spectral estimation for data sequences with missing samples is also important in many applications ranging from astronomical time series analysis to synthetic aperture radar imaging with angular diversity. For spectral estimation in the missing-data case, the challenge is how to extend the existing spectral estimation techniques to deal with these missing- data samples. Recently, nonparametric adaptive filtering based techniques have been developed successfully for various missing-data problems. Collectively, these algorithms provide a comprehensive toolset for the missing-data problem based exclusively on the nonparametric adaptive filter-bank approaches, which are robust and accurate, and can provide high resolution and low sidelobes. In this book, we present these algorithms for both one-dimensional and two- dimensional spectral estimation problems.

  • Skill Acquisition and Self-Improvement for Environmental Change Adaptation of Mobile Robot

    Learning and development are essential processes for an animat to adapt itself to environmental changes so as to accomplish a given task. This paper proposes a single mechanism for learning and self-improvement that results in learning curves similar to the “U-shape” phenomena observed in several psychological experiments concerning the human learning process such as in language acquisition. The basic idea is that (1) the animat monitors its success rate in goal achievement so as to perceive environmental changes instead of relying on signals from a teacher, and (2) in order to reuse acquired knowledge and accelerate reinforcement learning, the animat does not memorize the action values but transfers only the learned policy. The resultant policy (a state transition map where transitions indicate the best actions) may not be optimal in any given environment but it may be able to better handle differences between environments. We apply this model to a mobile robot navigation problem for which the task is to reach the target while avoiding obstacles by means of uninterpreted sonar and visual information. Our experimental results demonstrate the validity of the model.



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