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Impact of multipath in a hybrid TDoA/DoA sparse radiolocalization framework 20

Impact of multipath in a hybrid TDoA/DoA sparse radiolocaliz...

引用

20th International conference on Electromagnetics in Advanced applications, ICEAA 2018

作者： Hincapie, Roberto Gomez, Cristina Betancur, Leonardo Lavrenko, Anastasia Schmitz, Johannes Universidad Pontificia Bolivariana Medellín68305 Colombia

ISBN: (纸本)9781538667620

In this paper, we analyze a sparse framework for hybrid radiolocalization of multiple emitters in the presence of a simple multipath channel. The scenario under consideration includes multiple non-collaborative targets and multiple sensors with flexible TDoA/DoA capabilities. Scatterers surrounding the target nodes and the sensor nodes are assumed. The localization is performed as a joint block-sparse recovery problem. Partial combinations of hetereogeneous measurements provided by the sensors are performed in the fusion center. This approach has proven to provide a similar performance when compared to the fully joint recovery approach, decreasing the computational complexity of the algorithm. In this paper, our aim is to analyze the impact of simple multipath and some of the channel physical parameters, as the radio of the clusters and the number of scatterers, in the performance of the algorithms. © 2018 IEEE.

关键词： sensor nodes

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Towards robust 3D skeleton tracking using data fusion from multiple depth sensors 10

Towards robust 3D skeleton tracking using data fusion from m...

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10th International conference on Virtual Worlds and Games for Serious applications, VS-Games 2018

作者： Wu, Yuanjie Gao, Lei Hoermann, Simon Lindeman, Robert W. HIT Lab NZ University of Canterbury Christchurch New Zealand

ISBN: (纸本)9781538671238

Real-time full-body tracking in VR is important for providing realistic experiences, especially for applications such as training, education, and social VR. The Microsoft Kinect v2 sensor can provide skeleton data for a user in real-time, however, due to occlusion issues and front/back ambiguity errors, one Kinect is not always reliable enough for the correct capture of 360-degree movements. In this paper, we present work to provide robust, real-time tracking using multiple Kinect v2 cameras. An adaptive data fusion method is described that constructs a high-quality 3D skeleton which can be used to drive a VR avatar regardless of the user's orientation. We compare three different approaches to fusing the data from the three Kinects, and compare against ground truth using an OptiTrack system. A static pose and a dynamic movement were captured to compare errors of each joint using the three fusion algorithms. Our results show that an adaptive weighting adjustment fusion method for combining skeleton data from the three Kinects according to the current facing direction performed best in terms of joint error. © 2018 IEEE.

关键词： Virtual reality

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1st IEEE Colombian conference on applications in Computational Intelligence, ColCACI 2018

1st IEEE Colombian Conference on Applications in Computation...

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1st IEEE Colombian conference on applications in Computational Intelligence, ColCACI 2018

ISBN: (纸本)9783030030223

The proceedings contain 17 papers. The special focus in this conference is on applications in Computational Intelligence. The topics include: Comparison of evolutionary algorithms for estimation of parameters of the equivalent circuit of an AC motor;Cost-balance setting of MapReduce and spark-based architectures for SVM;nonlinear methodologies for climate studies in the Peruvian Northeast Coast;spectral image fusion for increasing the spatio-spectral resolution through side information;evaluation of a modified current selective harmonic elimination technique applied in low voltage power systems;about the effectiveness of teleconsults to evaluate the progress of type-2 diabetes and depression;optimal dimensioning of electrical distribution networks considering stochastic load demand and voltage levels;application of transfer learning for object recognition using convolutional neural networks;SOM-like neural network and differential evolution for multi-level image segmentation and classification in slit-lamp images;Implementation of a neural control system based on PI control for a non-linear process;filter banks as proposal in electrical motors fault discrimination;discrimination of nonlinear loads in electric energy generation systems using harmonic information;a systematic literature review of hardware neural networks;on computing the variance of a fuzzy number;eHealth services based on Monte Carlo algorithms to anticipate and lessen the progress of type-2 diabetes.

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Robot Intelligence Technology and applications 5: Results from the 5th International conference on Robot Intelligence Technology and applications

引用

2018年

作者： Jong-hwan Kim Hyun Myung Junmo Kim Weiliang Xu Eric T Matson Jin-woo Jung Han-lim Choi

ISBN: (纸本)9783319784519

This book includes papers from the 5th International conference on Robot Intelligence Technologyand applications held at KAIST, Daejeon, Korea on December 1315, 2017. It covers the following areas: artificial intelligence, autonomous robot navigation, intelligent robot system design, intelligent sensing and control, and machine vision. The topics included in this book are deep learning, deep neural networks, image understanding, natural language processing, speech/voice/text recognition, reasoning & inference, sensor integration/fusion/perception, multisensor data fusion, navigation/SLAM/localization, distributed intelligent algorithms and techniques, ubiquitous computing, digital creatures, intelligent agents, computer vision, virtual/augmented reality, surveillance, pattern recognition, gesture recognition, fingerprint recognition, animation and virtual characters, and emerging applications. This book is a valuable resource for robotics scientists, computer scientists, artificial intelligence researchers and professionals in universities, research institutes and laboratories.

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Anomaly Detection and Target Prioritization in Planetary Imagery via the Automated Global Feature Analyzer™ (AGFA™): Progress Towards a Driver for Autonomous C⁴ISR Missions

Anomaly Detection and Target Prioritization in Planetary Ima...

引用

conference on Micro- and Nanotechnology sensors, Systems, and applications X

作者： Fink, Wolfgang Brooks, Alexander J. -W. Tarbell, Mark A. Univ Arizona Coll Engn Visual & Autonomous Explorat Syst Res Lab 1230 E Speedway Blvd Tucson AZ 85721 USA

ISBN: (数字)9781510617902

ISBN: (纸本)9781510617902

The Automated Global Feature Analyzer (TM) (AGFA (TM)) is a generically applicable automated sensor-data-fusion, feature extraction, feature vector clustering, anomaly detection, and target prioritization framework. AGFA (TM) operates in the respective feature space delivered by the sensor(s). In this paper we provide an overview of the inner workings of AGFA (TM) and apply AGFA (TM) to planetary imagery, representative of past, current, and future planetary missions, to demonstrate its automated and objective (i.e., unbiased) anomaly detection and target prioritization (i.e., region-of interest delineation) capabilities. Imaged operational areas are locally processed via a cascade of image segmentation, visual and geometric feature extraction, agglomerative clustering, and principal components analysis. Resulting clusters are labeled based on relative size and location in feature space. Anomalous regions may be considered immediate targets for follow-up in-situ investigation by local robotic agents, which can be directed via autonomous telecommanding, e.g., as part of a Tier-Scalable Reconnaissance mission architecture. These capabilities will be essential for driving fully autonomous (CISR)-I-4 missions of the future, since the speed of light prohibits "real time" Earth-controlled conduct of planetary exploration beyond the Moon.

关键词： Autonomous decision making sensor-data-fusion framework objective anomaly detection target prioritization agglomerative clustering principal components analysis autonomous (CISR)-I-4 systems multi-tiered robotic exploration architectures

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Brain-Inspired Technologies: Towards Chips that Think? 65

Brain-Inspired Technologies: Towards Chips that Think?

引用

65th IEEE International Solid-State Circuits conference (ISSCC)

作者： De Salvo, Barbara Univ Grenoble Alpes CEA Leti Grenoble France

ISBN: (纸本)9781509049400

The advent of the Internet-of-Things has introduced a new paradigm that supports a decentralized and hierarchical communication architecture, where a great deal of analytics processing occurs at the edge and at the end-devices instead of in the Cloud. To map the embedded-systems requirements, we present a holistic research approach to the development of low-power architectures inspired by the human brain, where process development and integration, circuit design, system architecture, and learning algorithms are simultaneously optimized. This paper is organized as follows: We begin with a survey of recent research on the human brain and a historical perspective of cognitive neuroscience. Then, artificial intelligence is introduced, and the challenges of Deep Learning systems (in terms of power requirements) are addressed. The key reasons to distribute intelligence over the whole network are discussed. To emphasize the need for low-power solutions, a quantitative benchmark of existing specialized edge platforms that can execute machine-learning algorithms on conventional embedded hardware is presented. The primary focus of this paper will be on the implementation of optimized neuromorphic hardware as a highly promising solution for future ultra-low-power cognitive systems. We show that emerging technologies (such as advanced CMOS, 3D technologies, emerging resistive memories, and Silicon photonics), coupled with novel brain-inspired paradigms, such as spike-coding and spike-time-dependent-plasticity, have extraordinary potential to provide intelligent features in hardware, approaching the way knowledge is created and processed in the human brain. Finally, we conclude with our vision of the enabled future disruptive applications and a discussion of the main challenges which should be tackled to exploit the full potential of brain-inspired technologies.

关键词： Hardware Neurons Artificial intelligence Cognitive science Biological neural networks Wireless sensor networks Wireless communication

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Multi-sensor Attitude and Heading Reference System using Genetically Optimized Kalman Filter 61

Multi-sensor Attitude and Heading Reference System using Gen...

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61st IEEE International Midwest Symposium on Circuits and Systems (MWSCAS)

作者： Gessesse, Meron Atia, Mohamed M. Carleton Univ Dept Elect Ottawa ON Canada

ISBN: (纸本)9781538673928

An Attitude and Heading Reference System (AHRS) comprising accelerometers, gyroscopes and magnetometers can provide roll, pitch and heading information. AHRS is utilized in many applications such as navigation, augmented/virtual reality, and mobile mapping. The AHRS mechanization involves integration of angular rate measurement to provide high rate orientation but with unbounded drifts due to accumulation of random noise. To reduce drifts, mechanization output is combined with absolute measurement from magnetometer and accelerometer using Extended Kalman Filter(EKF). EKF accuracy is greatly affected by process covariance matrix (Q) and measurement noise covariance matrix(R). Conventional stochastic modeling approaches to determine Q and R parameters do not guarantee best performance. This paper proposes a systematic procedure for EKF parameters optimization using a hybrid statistical and genetic algorithms (GA) approach. The proposed approach has been verified on real data collected by an inertial measurement unit. Results showed that the Q and R can be optimized within few GA iterations outperforming conventional EKF parameter estimation methods.

关键词： Kalman Filter Navigation Estimation sensor fusion

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Accurate 3D Localization for MAV Swarms by UWB and IMU fusion 14

Accurate 3D Localization for MAV Swarms by UWB and IMU Fusio...

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14th IEEE International conference on Control and Automation (ICCA)

作者： Li, Jiaxin Bi, Yingcai Li, Kun Wang, Kangli Lin, Feng Chen, Ben M. Natl Univ Singapore NUS NUS Grad Sch Integrat Sci & Engn Singapore Singapore NUS Dept Elect & Comp Engn Singapore Singapore NUS Temasek Lab Singapore Singapore

ISBN: (纸本)9781538660898

Driven by applications like Micro Aerial Vehicles (MAVs), driver-less cars, etc, localization solution has become an active research topic in the past decade. In recent years, Ultra Wideband (UWB) emerged as a promising technology because of its impressive performance in both indoor and outdoor positioning. But algorithms relying only on UWB sensor usually result in high latency and low bandwidth, which is undesirable in some situations such as controlling a MAV. To alleviate this problem, an Extended Kalman Filter (EKF) based algorithm is proposed to fuse the Inertial Measurement Unit (IMU) and UWB, which achieved 80Hz 3D localization with the significantly improved accuracy and almost no delay. To verify the effectiveness and reliability of the proposed approach, a swarm of 6 MAVs is set up to perform a light show in an indoor exhibition hall.

关键词： Acceleration Distance measurement Position measurement Noise measurement Global Positioning System Wireless fidelity ZigBee"

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Fusing Sonars and LRF Data to Glass Detection for Robotics Navigation

Fusing Sonars and LRF Data to Glass Detection for Robotics N...

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IEEE International conference on Robotics and Biomimetics (ROBIO)

作者： Wei, Hao Li, Xueen Shi, Ying You, Bo Xu, Yi Univ Chinese Acad Sci Beijing Peoples R China Inst Automat CAS Beijing Peoples R China Chinese Acad Sci Inst Automat Beijing Peoples R China

ISBN: (纸本)9781728103778

Identifying and detecting glass is an important part of robotic safety at office conditions. Existing glass detection algorithms rely on high-cost lidars or ultrasonic rings. We propose an efficient and simple algorithm to detect glass based on sensor fusion of ultrasound sensors and laser scanners data that can adapts to all kinds of lidars. Combine the glass detection results with gmapping algorithm to generate a more accurate map, the maximum connected domain algorithm used to remove noise from the map. We tested the glass detection algorithm on the robot platform. Experiments showed that about 93% of the glass can be detected correctly.

关键词： Ultrasonic applications

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On Universal sensor Registration

On Universal Sensor Registration

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International conference on Information fusion

作者： Daniel Sigalov Aharon Gal Boaz Vigdor Rafael - Advanced Defense Systems Israel

We present a simple approach for sensor registration in target tracking applications. The proposed method uses targets of opportunity and, without making assumptions on their dynamical models, allows simultaneous calibration of multiple three- and two-dimensional sensors. Whereas for two-sensor scenarios only relative registration is possible, in practical cases with three or more sensors unambiguous absolute calibration may be achieved. The derived algorithms are straightforward to implement and do not require tuning of parameters. The performance of the algorithms is tested in a numerical study.

关键词： sensor registration Bias calibration sensor misalignment

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