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conference on Multisensor, Multisource Information fusion - architectures, algorithms, and applications

作者： Long, Jiang Wang, Bingnan Mitsubishi Elect Res Labs Cambridge MA 02139 USA

ISBN: (纸本)9781628410587

This paper reports a metamaterial inspired combined inductive-capacitive sensing method for detecting and distinguishing metallic and non-metallic objects. Metallic and non-metallic objects can be distinguished by measuring both of their inductive and capacitive responses based on the fact that they respond differently to inductive and capacitive sensing. The proposed method is inspired by metamaterial structures. Both inductive and capacitive sensing are simultaneously realized when the sensor is operating at off-resonant frequencies. The proposed method is demonstrated with typical printed circuit board (PCB) technology. The designed sensor can distinguish the metallic and dielectric objects with a sensing range about 10 mm, showing a competitive performance compared with commercially available proximity sensors.

关键词： proximity sensor metamaterials combined sensing

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IVVI 2.0: An intelligent vehicle based on computational perception

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EXPERT SYSTEMS WITH applications 2014年第17期41卷 7927-7944页

作者： Martin, D. Garcia, F. Musleh, B. Olmeda, D. Pelaez, G. Marin, P. Ponz, A. Rodriguez, C. Al-Kaff, A. de la Escalera, A. Armingol, J. M. Univ Carlos III Madrid Intelligent Syst Lab Leganes Spain

This paper presents the IVVI 2.0 a smart research platform to foster intelligent systems in vehicles. Computational perception in intelligent transportation systems applications has advantages, such as huge data from vehicle environment, among others, so computer vision systems and laser scanners are the main devices that accomplish this task. Both have been integrated in our intelligent vehicle to develop cutting-edge applications to cope with perception difficulties, data processing algorithms, expert knowledge, and decision-making. The long-term in-vehicle applications, that are presented in this paper, outperform the most significant and fundamental technical limitations, such as, robustness in the face of changing environmental conditions. Our intelligent vehicle operates outdoors with pedestrians and others vehicles, and outperforms illumination variation, i.e.: shadows, low lighting conditions, night vision, among others. So, our applications ensure the suitable robustness and safety in case of a large variety of lighting conditions and complex perception tasks. Some of these complex tasks are overcome by the improvement of other devices, such as, inertial measurement units or differential global positioning systems, or perception architectures that accomplish sensor fusion processes in an efficient and safe manner. Both extra devices and architectures enhance the accuracy of computational perception and outreach the properties of each device separately. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Intelligent transportation systems Computer vision IR detection Data fusion Vehicle positioning

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Multisensor fusion with non-optimal decision rules: the challenges of "open world" sensing

Multisensor fusion with non-optimal decision rules: the chal...

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conference on Multisensor, Multisource Information fusion - architectures, algorithms, and applications

作者： Minor, Christian Johnson, Kevin Nova Res Inc Alexandria VA 22308 USA Naval Res Lab Washington DC 20375 USA

ISBN: (纸本)9781628410587

In this work, simple, generic models of chemical sensing are used to simulate sensor array data and to illustrate the impact on overall system performance that specific design choices impart. The ability of multisensor systems to perform multianalyte detection (i.e., distinguish multiple targets) is explored by examining the distinction between fundamental design-related limitations stemming from mismatching of mixture composition to fused sensor measurement spaces, and limitations that arise from measurement uncertainty. Insight on the limits and potential of sensor fusion to robustly address detection tasks in realistic field conditions can be gained through an examination of a) the underlying geometry of both the composition space of sources one hopes to elucidate and the measurement space a fused sensor system is capable of generating, and b) the informational impact of uncertainty on both of these spaces. For instance, what is the potential impact on sensor fusion in an open world scenario where unknown interferants may contaminate target signals? Under complex and dynamic backgrounds, decision rules may implicitly become non-optimal and adding sensors may increase the amount of conflicting information observed. This suggests that the manner in which a decision rule handles sensor conflict can be critical in leveraging sensor fusion for effective open world sensing, and becomes exponentially more important as more sensors are added. Results and design considerations for handling conflicting evidence in Bayes and Dempster-Shafer fusion frameworks are presented. Bayesian decision theory is used to provide an upper limit on detector performance of simulated sensor systems.

关键词： multisensor systems data fusion interferants open-world sensing Dempster-Shafer theory

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MTS in False Positive Reduction for Multi-sensor fusion

MTS in False Positive Reduction for Multi-Sensor Fusion

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conference on Multisensor, Multisource Information fusion - architectures, algorithms, and applications

作者： Woodley, Robert Gosnell, Michael Cudney, Elizabeth 21st Century Syst Inc Omaha NE 68106 USA

ISBN: (纸本)9781628410587

The Mahalanobis Taguchi System (MTS) is a relatively new tool in the vehicle health maintenance domain, but has some distinct advantages in current multi-sensor implementations. The use of Mahalanobis Spaces (MS) allows the algorithm to identify characteristics of sensor signals to identify behaviors in machines. MTS is extremely powerful with the caveat that the correct variables are selected to form the MS. In this research work, 56 sensors monitor various aspects of the vehicles. Typically, using the MTS process, identification of useful variables is preceded by validation of the measurements scale. However, the MTS approach doesn't directly include any mitigating steps should the measurement scale not be validated. Existing work has performed outlier removal in construction of the MS, which can lead to better validation. In our approach, we modify the outlier removal process with more liberal definitions of outliers to better identify variables' impact prior to identification of useful variables. This subtle change substantially lowered the false positive rate due to the fact that additional variables were retained. Traditional MTS approaches identify useful variables only to the extent they provide usefulness in identifying the positive (abnormal) condition. The impact of removing false negatives is not included. Initial results show our approach can reduce false positive values while still maintaining complete fault identification for this vehicle data set.

关键词： Mahalanobis-Taguchi System Multi-sensor fusion Variable Selection Threshold Selection Vehicle Health Maintenance Fault Detection False Positive Reduction Comparison of Methods

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Towards a unified architecture for mapping static environments 17

Towards a unified architecture for mapping static environmen...

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17th International conference on Information fusion (fusion)

作者： Kubertschak, Tim Maehlisch, Mirko Wuensche, Hans-Joachim AUDI AG I EE 31 D-85045 Ingolstadt Germany Univ Bundeswehr Munchen TAS D-85577 Neubiberg Germany

ISBN: (纸本)9781479916344

sensor fusion systems are becoming more and more important in automotive applications, especially for future driver assistance systems and autonomous driving. While it was sufficient to use single sensors in early driving assistance systems, future systems will rely on several sensors with different measurement principles. The probably conflicting measurements need to be fused to retrieve a complete picture of the current surroundings. However, an increased number of sensors leads to difficulties while incorporating their measurements, since every sensor provides its data via special interfaces. This inconvenience of current sensor fusion architectures has been solved for moving objects. A fusion architecture based on a generic interface the object list - has been developed over the last years. It allows an easy use of additional sensors as long as they provide their measurements as object lists. Similar solutions for static environments are rare, but the recent proposal of the Fences approach [1] is promising. This work shows, how sensors and occupancy grids are represented in the Fences-architecture. Steps and algorithms are presented to transform sensor reading into Fences as well as extracting Fences from common grid-based strategies for mapping static environments. The algorithms are applied to the conversion of ultrasonic sensor readings and LiDAR measurements to Fences. Furthermore, the construction of Fences from Bayesian occupancy grids is presented.

关键词： Advanced Driving Assistance Systems Multisensor Data fusion Static Environment Unified Architecture

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TDA2X, A SOC OPTIMIZED FOR ADVANCED DRIVER ASSISTANCE SYSTEMS

TDA2X, A SOC OPTIMIZED FOR ADVANCED DRIVER ASSISTANCE SYSTEM...

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IEEE International conference on Acoustics, Speech and Signal Processing (ICASSP)

作者： Sankaran, Jagadeesh Zoran, Nikolic Texas Instruments Inc Dallas TX 13532 USA

ISBN: (纸本)9781479928934

TDA2X is an optimized scalable system on chip (SoC) solution from Texas Instruments that spans various application areas of ADAS such as front-camera, surround-view and the emerging area of sensor fusion. It accomplishes this through a focused set of heterogeneous processors, brought together in a scalable architecture with a rich set of integrated peripherals, providing an optimal mix of performance in a low power footprint for Advanced Driver Assistance Systems (ADAS) vision analytics. Computer vision algorithms across the various ADAS application systems have a rich variation and diversity in processing requirements along with the need to run them concurrently within challenging thermal budgets. A heterogeneous architecture with various programmable elements allows system developers to map various portions of the algorithms to the architectures that are best suited for the underlying task allowing maximizing system performance and reducing development time and effort in developing these complex systems. Scalability of the architecture by varying the number of cores and clock speeds of these heterogeneous architectures, allows for scalability in performance and power across low, mid and high end products with one software investment. A critical focus on functional safety across the cores and various memories is particularly essential given the mission critical nature of ADAS applications.

关键词： ADAS SoC Front Camera Surround View sensor fusion and Programmable Vision Accelerators

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Cluster-Based Time Synchronization Protocol for Wireless sensor Networks

Cluster-Based Time Synchronization Protocol for Wireless Sen...

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14th International conference on algorithms and architectures for Parallel Processing (ICA3PP)

作者： Zhang, Jian Lin, Shiping Liu, Dandan Wuhan Univ Comp Sch Wuhan 430072 Peoples R China

ISBN: (纸本)9783319111971;9783319111964

Time synchronization is one of the most important premises for many applications in wireless sensor networks, including data fusion, target tracking, military surveillance, etc. Existing protocols generally suffered from higher energy consumption, worse accuracy or applicable only in small wireless sensor networks. In this paper, we propose a novel cluster based time synchronization method for large-scale wireless sensor networks. First, a cluster tree is constructed as the backbone. Then, after network clustering is completed, different time synchronization mechanisms are applied within cluster head nodes and cluster members, respectively. The theoretical analysis and simulation results show that the proposed algorithm can effectively reduce energy consumption comparing to existing protocols, while it also achieves the high accuracy of time synchronization.

关键词： Time synchronization clustering energy efficient wireless sensor networks

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Eliminating Mutual Views in fusion of Ranging and RGB-D Data From Robot Teams Operating in Confined Areas

Eliminating Mutual Views in Fusion of Ranging and RGB-D Data...

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conference on Multisensor, Multisource Information fusion - architectures, algorithms, and applications

作者： Lyons, Damian M. Shrestha, Karma Fordham Univ Robot & Comp Vis Lab Bronx NY 10458 USA

ISBN: (纸本)9781628410587

We address the problem of fusing laser and RGB-Data from multiple robots operating in close proximity to one another. By having a team of robots working together, a large area can be scanned quickly, or a smaller area scanned in greater detail. However, a key aspect of this problem is the elimination of the spurious readings due to the robots operating in close proximity. While there is an extensive literature on the mapping and localization aspect of this problem, our problem differs from the dynamic map problem in that it involves at one kind of transient map feature, robots viewing other robots, and we know that we wish to completely eliminate all such mutual views. In prior work, we investigated the problem of fusing laser data from multiple robots in such a manner as to reject this spurious data from other robots. This work showed that a combination of local robot-based direction filtering and global map-based visibility filtering at a central map server removed 91% of the spurious data and resulted in a 98% quality improvement. In this paper we additionally consider the problem of fusing RGB-D data generated by a stereo-camera sensor. An approach based on a model of human visual attention is presented and compared with our prior work and with other related work. This approach is an order of magnitude faster than the prior work and yet rejects 73% of the spurious data producing a 55% quality improvement. Results are shown for this approach for two experiments with a two robot team operating in a confined indoor environment (4m x 4m).

关键词： cognitive robotics navigation sensory fusion

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Cooperative and Self Organizing Paradigm for Wide Area Synchronized Monitoring of Smart Grids: performance analysis in real operating scenarios

Cooperative and Self Organizing Paradigm for Wide Area Synch...

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IEEE International Instrumentation and Measurement Technology conference (I2MTC)

作者： Capriglione, Domenico Ferrigno, Luigi Paciello, Vincenzo Pietrosanto, Antonio Vaccaro, Alfredo Univ Cassino DIEI I-03043 Cassino Italy Univ Salerno DIIn Fisciano Italy Univ Sannio Dept Engn Benevento Italy

ISBN: (纸本)9781467363860

Synchronized Wide-Area Monitoring Systems (WAMS) are very important in the development and the use of power system-wide measurements to avoid large disturbances and reduce the probability of catastrophic events. Typically in WAMS the global absolute time reference for sensors synchronization is obtained by satellite-based timing signals processing. Since these signals are extremely vulnerable to radiofrequency interference, effective countermeasures aimed at increasing the resilience of synchronized WAMS to external and internal interferences need to be designed. To this aim several synchronization approaches are explored in literature. In particular, to avoid the large volume of raw data involved in typical client-server architectures, many researchers are analyzing the possibility offered by decentralized architecture based on consensus policies. In this scenario many consensus-based synchronization methods are proposed in literature but the attention has rarely been paid to the influence factors that characterize real environments and real smart grid applications as: (i) the presence of hardware characterized by finite processing time, and finite resolution of nodes involved in the consensus procedure;(ii) the effect of typical clock instability as drift, jitter and wander;(iii) the effect of latencies and limited bandwidths available on a radio system or when common commercial wireless communication are adopted. All the above-mentioned influence factors can be thought of as causes of uncertainties that could affect the overall performance. This paper proposes a study these influence factors both in simulated and real scenarios. The final aim is to find an uncertainty model to evaluate and forecast the reliability and the quality of the time synchronization procedure.

关键词： Smart grid Consensus sensor Network Time Synchronization data fusion measurement uncertainty

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Towards a unified architecture for mapping static environments

Towards a unified architecture for mapping static environmen...

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International conference on Information fusion

作者： Tim Kubertschak Mirko Maehlisch Hans-Joachim Wuensche AUDI AG I/EE-31 Ingolstadt Germany

sensor fusion systems are becoming more and more important in automotive applications, especially for future driver assistance systems and autonomous driving. While it was sufficient to use single sensors in early driving assistance systems, future systems will rely on several sensors with different measurement principles. The probably conflicting measurements need to be fused to retrieve a complete picture of the current surroundings. However, an increased number of sensors leads to difficulties while incorporating their measurements, since every sensor provides its data via special interfaces. This inconvenience of current sensor fusion architectures has been solved for moving objects. A fusion architecture based on a generic interface - the object list - has been developed over the last years. It allows an easy use of additional sensors as long as they provide their measurements as object lists. Similar solutions for static environments are rare, but the recent proposal of the Fences-approach [1] is promising. This work shows, how sensors and occupancy grids are represented in the Fences-architecture. Steps and algorithms are presented to transform sensor reading into Fences as well as extracting Fences from common grid-based strategies for mapping static environments. The algorithms are applied to the conversion of ultrasonic sensor readings and LiDAR measurements to Fences. Furthermore, the construction of Fences from Bayesian occupancy grids is presented.

关键词： Uncertainty sensor phenomena and characterization Vehicles sensor fusion Acoustics Robot sensing systems

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