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Multi-robot Terrain Coverage and Task Allocation For Autonomous detection of Landmines

Multi-robot Terrain Coverage and Task Allocation For Autonom...

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Conference on Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense XI

作者： Dasgupta, Prithviraj Munoz-Melendez, Angelica Guruprasad, K. R. Univ Nebraska Dept Comp Sci Omaha NE 68182 USA

ISBN: (纸本)9780819490377

Multi-robot systems comprising of heterogeneous autonomous vehicles on land, air, water are being increasingly used to assist or replace humans in different hazardous missions. Two crucial aspects in such multi-robot systems are to: a) explore an initially unknown region of interest to discover tasks, and, b) allocate and share the discovered tasks between the robots in a coordinated manner using a multi-robot task allocation (MRTA) algorithm. In this paper, we describe results from our research on multi-robot terrain coverage and MRTA algorithms within an autonomous landmine detection scenario, done as part of the COMRADES project. Each robot is equipped with a different type of landmine detection sensor and different sensors, even of the same type, can have different degrees of accuracy. The landmine detection-related operations performed by each robot are abstracted as tasks and multiple robots are required to complete a single task. First, we describe a distributed and robust terrain coverage algorithm that employs Voronoi partitions to divide the area of interest among the robots and then uses a single-robot coverage algorithm to explore each partition for potential landmines. Then, we describe MRTA algorithms that use the location information of discovered potential landmines and employ either a greedy strategy, or, an opportunistic strategy to allocate tasks among the robots while attempting to minimize the time (energy) expended by the robots to perform the tasks. We report experimental results of our algorithms using accurately-simulated Corobot robots within the Webots simulator performing a multi-robot, landmine detection operation.

关键词： Robots Land mines Sensors Stochastic processes Metals Computer simulations detection and tracking algorithms Agriculture General packet radio service Mobile robots

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Coherent Integration of Optical Interferometric Data on a Graphics Processor

Coherent Integration of Optical Interferometric Data on a Gr...

引用

Conference on Optical and Infrared Interferometry III

作者： Paiz, M. Jorgensen, A. M. New Mexico Inst Min & Technol Socorro NM 87801 USA

ISBN: (纸本)9780819491466

Coherent integration is central to extracting maximum signal-to-noise ratio (SNR) from optical interferometric data, with post-processing being the most effective method. More sophisticated algorithms produce better results, but also use more computing time, sometimes as much as several minutes of computing time per second of obser- vation. As data volumes continue to increase, it is becoming impractical to transfer the data to a supercomputer. To address this problem, we have explored using a General Purpose Graphics Processor (GPGPU) to perform these computations on a local machine, exploiting the fact that the problem is, in principle, massively parallel. In this paper, we discuss methods to optimize the fringe-tracking algorithm. In particular, we emphasize the parameter extraction process, and describe implementations using both genetic algorithms and Powells method. Using these methods, we were able to improve performance by a factor of 100.

关键词： Genetic algorithms Interferometry Signal to noise ratio Integrated optics Visualization Visibility detection and tracking algorithms Optimization (mathematics) Profiling Genetics

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Recovering shapes of specular objects in motion via normal vector map consistency

Recovering shapes of specular objects in motion via normal v...

引用

Conference on Interferometry XVI - Techniques and Analysis

作者： Pak, Alexey Fraunhofer IOSB D-76131 Karlsruhe Germany

ISBN: (纸本)9780819492104

We present a novel method to reconstruct the shape of a moving specular object from multiple camera images taken near a calibrated display with a known color-encoded pattern. The method is based on voxel carving exploiting the consistency of the cones of allowed normal vectors, or normal vector maps (NVMs). The algorithm is highly parallel, does not rely on pattern recognition and applies to surfaces of arbitrary complexity.

关键词： Cameras Algorithm development Raster graphics detection and tracking algorithms Inspection Reconstruction algorithms Reflection Solids Visualization Calibration

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Face Recognition from a Moving Platform via Sparse Representation

Face Recognition from a Moving Platform via Sparse Represent...

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Conference on Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering X

作者： Hsu, Ming Kai Hsu, Charles Lee, Ting N. Szu, Harold George Washington Univ ECE Dept Washington DC 20052 USA

ISBN: (纸本)9780819490797

A video-based surveillance system for passengers includes face detection, face tracking and face recognition. In general, the final recognition result of the video-based surveillance system is usually determined by the cumulative recognition results. Under this strategy, the correctness of face tracking plays an important role for the system recognition rate. For face tracking, the challenges of face tracking on a moving platform are that the space and time information used for conventional face tracking algorithms may be lost. Consequently, conventional face tracking algorithms can barely handle the face tracking on a moving platform. In this paper, we have verified the state-of-the-art technologies for face detection, face tracking and face recognition on a moving platform. In the mean time, we also proposed a new strategy for face tracking on a moving platform or face tracking under very low frame rate. The steps of the new strategy for face detection are: (1) classification the detected faces over a certain period instead of every frame (2) tracking of each passenger is equivalent to reconstruct the time order of certain period for each passenger. If the cumulative recognition results are the only part needed for the surveillance system, step 2 can be skipped. In addition, if the additional information from the passengers is required, such as path tracking, lip read, gesture recognition, etc, time order reconstruction in step 2 can offer the information required.

关键词： Facial recognition systems Video Video surveillance detection and tracking algorithms Surveillance systems Sensors Algorithm development Machine vision Surveillance Reconstruction algorithms

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Fully Self-Contained Vision-Aided Navigation and Landing of a Micro Air Vehicle Independent from External Sensor Inputs

Fully Self-Contained Vision-Aided Navigation and Landing of ...

引用

Conference on Unmanned Systems Technology XIV

作者： Brockers, Roland Susca, Sara Zhu, David Matthies, Larry CALTECH Jet Prop Lab Pasadena CA 91125 USA

ISBN: (纸本)9780819490650

Direct-lift micro air vehicles have important applications in reconnaissance. In order to conduct persistent surveillance in urban environments, it is essential that these systems can perform autonomous landing maneuvers on elevated surfaces that provide high vantage points without the help of any external sensor and with a fully contained on-board software solution. In this paper, we present a micro air vehicle that uses vision feedback from a single down looking camera to navigate autonomously and detect an elevated landing platform as a surrogate for a roof top. Our method requires no special preparation (labels or markers) of the landing location. Rather, leveraging the planar character of urban structure, the landing platform detection system uses a planar homography decomposition to detect landing targets and produce approach waypoints for autonomous landing. The vehicle control algorithm uses a Kalman filter based approach for pose estimation to fuse visual SLAM (PTAM) position estimates with IMU data to correct for high latency SLAM inputs and to increase the position estimate update rate in order to improve control stability. Scale recovery is achieved using inputs from a sonar altimeter. In experimental runs, we demonstrate a real-time implementation running on-board a micro aerial vehicle that is fully self-contained and independent from any external sensor information. With this method, the vehicle is able to search autonomously for a landing location and perform precision landing maneuvers on the detected targets.

关键词： Sensors Sensor fusion Micro unmanned aerial vehicles Navigation systems Target detection Cameras Visualization detection and tracking algorithms Control systems Vehicle control

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Evaluating the Efficiency of a Night-Time, Middle-Range Infrared Sensor for Applications in Human detection and Recognition

Evaluating the Efficiency of a Night-Time, Middle-Range Infr...

引用

Conference on Infrared Imaging Systems - Design, Analysis, Modeling, and Testing XXIII

作者： Bourlai, Thirimachos Von Dollen, John Mavridis, Nikolaos Kolanko, Christopher W Virginia Univ POB 6201 Morgantown WV 26506 USA

ISBN: (纸本)9780819490339

In law enforcement and security applications, the acquisition of face images is critical in producing key trace evidence for the successful identification of potential threats. In this work we, first, use a near infrared (NIR) sensor designed with the capability to acquire images at middle-range stand-off distances at night. Then, we determine the maximum stand-off distance where face recognition techniques can be utilized to efficiently recognize individuals at night at ranges from 30 to approximately 300 ft. The focus of the study is on establishing the maximum capabilities of the mid-range sensor to acquire good quality face images necessary for recognition. For the purpose of this study, a database in the visible (baseline) and NIR spectrum of 103 subjects is assembled and used to illustrate the challenges associated with the problem. In order to perform matching studies, we use multiple face recognition techniques and demonstrate that certain techniques are more robust in terms of recognition performance when using face images acquired at different distances. Experiments show that matching NIR face images at longer ranges (i.e. greater than about 300 feet or 90 meters using our camera system) is a very challenging problem and it requires further investigation.

关键词： Near infrared Cameras Facial recognition systems Imaging systems Databases Video detection and tracking algorithms Eye Sensors Visible radiation

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Kernel Sparse Representation for Hyperspectral Target detection

Kernel Sparse Representation for Hyperspectral Target Detect...

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Annual Conference on algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII

作者： Chen, Yi Nasrabadi, Nasser M. Tran, Trac D. Johns Hopkins Univ Dept Elect & Comp Engn 3400 N Charles St Baltimore MD 21218 USA US Army Res Lab Adelphi MD 20783 USA

ISBN: (纸本)9780819490681

A nonlinear kernel-based classifier for hyperspectral target detection is proposed in this paper. The proposed approach relies on sparsely representing a test sample in terms of all the training samples in a high-dimensional feature space induced by a kernel function. Specifically, the feature representation of a test pixel is assumed to be compactly expressed as a sparse linear combination of few atoms from a training dictionary consisting of both background and target training samples in the same feature space. The sparse representation vector is obtained by decomposing the test pixel over the training dictionary via a kernelized greedy algorithm, which uses the kernel trick to avoid explicit evaluations of the data in the feature space. The class label is then determined by comparing the reconstruction accuracy with respect to the background and target sub-dictionaries using the recovered sparse vector. Designing the classifier in a high-dimensional feature subspace will implicitly exploit the higher-order structure (correlations) within the data which cannot be captured by a linear model. Therefore, by projecting the pixels into a kernel feature space and kernelizing the linear sparse representation model, the data separability between the background and target classes will be shown to be improved, leading to a more accurate detection performance. The effectiveness of the proposed kernel sparsity model for target detection is demonstrated by experimental results on real hyperspectral images.

关键词： detection and tracking algorithms Associative arrays Target detection Sensors Chemical species Hyperspectral target detection Data modeling Dubnium Hyperspectral imaging Reconstruction algorithms

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Application of Dynamic Logic Algorithm to Analyze AFRL Gotcha Data

Application of Dynamic Logic Algorithm to Analyze AFRL Gotch...

引用

Conference on Cyber Sensing

作者： Lin, Freeman C. Perlovsky, Leonid I. USAF Res Lab Sensor Directorate Wright Patterson AFB OH 45433 USA

ISBN: (纸本)9780819490865

In this paper, we apply Dynamic Logic algorithm (DL) directly to analyze AFRL Gotcha raw data, which are sampled in terms of chirp frequencies for each pulse. This approach has not been done in the existing literature because previously, there is no visual or conceptual interpretation how to detect ground moving targets directly from synthetic aperture radar (SAR) raw data. Using Gotcha raw data taken from the severe radar clutter environment, we have demonstrated that DL not only maintains its robustness in terms of detecting small ground moving targets but also provides the effectiveness to extract specific features such as shape, size, location (along the range swath), movement direction, and traveling speed for the desired target.

关键词： Synthetic aperture radar Device simulation Target detection Data modeling Radar Virtual colonoscopy Roads detection and tracking algorithms Logic Statistical modeling

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Predictable turn-around time for Post Tape-Out Flow

Predictable turn-around time for Post Tape-Out Flow

引用

Conference on Optical Microlithography XXV

作者： Endo, Toshi Park, Minyoung Ghosh, Pradiptya Mentor Graph Corp Fremont CA 94538 USA

ISBN: (纸本)9780819489821

A typical post-out flow data path at the IC Fabrication has following major components of software based processing - Boolean operations before the application of resolution enhancement techniques (RET) and optical proximity correctin (OPC), the RET and OPC step [etch retargeting, sub-resolution assist feature insertion (SRAF) and OPC], post-OPCRET Boolean operations and sometimes in the same flow simulation based verification. There are two objectives that an IC Fabrication tapeout flow manager wants to achieve with the flow - predictable completion time and fastest turn-around time (TAT). At times they may be competing. There have been studies in the literature modeling the turn-around time from historical data for runs with the same recipe and later using that to derive the resource allocation for subsequent runs. [3]. This approach is more feasible in predominantly simulation dominated tools but for edge operation dominated flow it may not be possible especially if some processing acceleration methods like pattern matching or hierarchical processing is involved. In this paper, we suggest an alternative method of providing target turnaround time and managing the priority of jobs while not doing any upfront resource modeling and resource planning. The methodology then systematically either meets the turnaround time need and potentially lets the user know if it will not as soon as possible. This builds on top of the Calibre Cluster Management (CalCM) resource management work previously published [1][2]. The paper describes the initial demonstration of the concept.

关键词： Data processing Computer simulations Data modeling Optical proximity correction Resolution enhancement technologies Control systems detection and tracking algorithms Photomasks SRAF Computing systems

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Robust registration of sparsely sectioned histology to ex-vivo MRI of temporal lobe resections

Robust registration of sparsely sectioned histology to ex-vi...

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Conference on Medical Imaging - Image Processing

作者： Goubran, Maged Khan, Ali R. Crukley, Cathie Buchanan, Susan Santyr, Brendan deRibaupierre, Sandrine Peters, Terence M. Univ Western Ontario Robarts Res Inst Imaging Res Labs London ON Canada Univ Western Ontario Dept Clin Neurol Sci London ON Canada Univ Western Ontario Dept Biomed Engn London ON Canada

ISBN: (纸本)9780819489630

Surgical resection of epileptic foci is a typical treatment for drug-resistant epilepsy, however, accurate pre-operative localization is challenging and often requires invasive sub-dural or intra-cranial electrode placement. The presence of cellular abnormalities in the resected tissue can be used to validate the effectiveness of multispectral Magnetic Resonance Imaging (MRI) in pre-operative foci localization and surgical planning. If successful, these techniques can lead to improved surgical outcomes and less invasive procedures. Towards this goal, a novel pipeline is presented here for post-operative imaging of temporal lobe specimens involving MRI and digital histology, and present and evaluate methods for bringing these images into spatial correspondence. The sparsely-sectioned histology images of resected tissue represents a challenge for 3D reconstruction which we address with a combined 3D and 2D rigid registration algorithm that alternates between slice-based and volume-based registration with the ex-vivo MRI. We also evaluate four methods for non-rigid within-plane registration using both images and fiducials, with the top performing method resulting in a target registration error of 0.87 mm. This work allows for the spatially-local comparison of histology with post-operative MRI and paves the way for eventual registration with pre-operative MRI images.

关键词： Magnetic resonance imaging Image registration Tissues Image processing detection and tracking algorithms Epilepsy 3D image processing 3D modeling Surgery Reconstruction algorithms

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