Visual metrics for the evaluation of sensor data quality in outdoor perception

This paper proposes an experimental study of quality metrics that can be applied to visual and infrared images acquired from cameras onboard an unmanned ground vehicle (UGV). The relevance of existing metrics in this context is discussed and a novel metric is introduced. Selected metrics are evaluated on data collected by a UGV in clear and challenging environmental conditions, represented in this paper by the presence of airborne dust or smoke. An example of application is given with monocular SLAM estimating the pose of the UGV while smoke is present in the environment. It is shown that the proposed novel quality metric can be used to anticipate situations where the quality of the pose estimate will be significantly degraded due to the input image data. This leads to decisions of advantageously switching between data sources (e.g. using infrared images instead of visual images).

Visual metrics for the evaluation of sensor data quality in outdoor perception

This paper proposes an experimental study of quality metrics that can be applied to visual and infrared images acquired from cameras onboard an unmanned ground vehicle (UGV). The relevance of existing metrics in this context is discussed and a novel metric is introduced. Selected metrics are evaluated on data collected by a UGV in clear and challenging environmental conditions, represented in this paper by the presence of airborne dust or smoke.

Datasets for the evaluation of multi-sensor perception in natural environments with challenging conditions

This paper presents large, accurately calibrated and time-synchronised datasets, gathered outdoors in controlled environmental conditions, using an unmanned ground vehicle (UGV), equipped with a wide variety of sensors. It discusses how the data collection process was designed, the conditions in which these datasets have been gathered, and some possible outcomes of their exploitation, in particular for the evaluation of performance of sensors and perception algorithms for UGVs.

Sensor Data Integrity : Multi-Sensor Perception for Unmanned Ground Vehicles

This document describes large, accurately calibrated and time-synchronised datasets, gathered in controlled environmental conditions, using an unmanned ground vehicle equipped with a wide variety of sensors. These sensors include: multiple laser scanners, a millimetre wave radar scanner, a colour camera and an infra-red camera. Full details of the sensors are given, as well as the calibration parameters needed to locate them with respect to each other and to the platform. This report also specifies the format and content of the data, and the conditions in which the data have been gathered. The data collection was made in two different situations of the vehicle: static and dynamic. The static tests consisted of sensing a fixed ’reference’ terrain, containing simple known objects, from a motionless vehicle. For the dynamic tests, data were acquired from a moving vehicle in various environments, mainly rural, including an open area, a semi-urban zone and a natural area with different types of vegetation. For both categories, data have been gathered in controlled environmental conditions, which included the presence of dust, smoke and rain. Most of the environments involved were static, except for a few specific datasets which involve the presence of a walking pedestrian. Finally, this document presents illustrations of the effects of adverse environmental conditions on sensor data, as a first step towards reliability and integrity in autonomous perceptual systems.

Combining multiple sensor modalities for a localisation robust to smoke

This paper proposes an approach to obtain a localisation that is robust to smoke by exploiting multiple sensing modalities: visual and infrared (IR) cameras. This localisation is based on a state-of-the-art visual SLAM algorithm. First, we show that a reasonably accurate localisation can be obtained in the presence of smoke by using only an IR camera, a sensor that is hardly affected by smoke, contrary to a visual camera (operating in the visible spectrum). Second, we demonstrate that improved results can be obtained by combining the information from the two sensor modalities (visual and IR cameras). Third, we show that by detecting the impact of smoke on the visual images using a data quality metric, we can anticipate and mitigate the degradation in performance of the localisation by discarding the most affected data. The experimental validation presents multiple trajectories estimated by the various methods considered, all thoroughly compared to an accurate dGPS/INS reference.

The Marulan data sets: multi-sensor perception in a natural environment with challenging conditions

In this paper we present large, accurately calibrated and time-synchronized data sets, gathered outdoors in controlled and variable environmental conditions, using an unmanned ground vehicle (UGV), equipped with a wide variety of sensors. These include four 2D laser scanners, a radar scanner, a color camera and an infrared camera. It provides a full description of the system used for data collection and the types of environments and conditions in which these data sets have been gathered, which include the presence of airborne dust, smoke and rain.

Strain engineering of selective chemical adsorption on monolayer MoS2

Nanomaterials are prone to influence by chemical adsorption because of their large surface to volume ratios. This enables sensitive detection of adsorbed chemical species which, in turn, can tune the property of the host material. Recent studies discovered that single and multi-layer molybdenum disulfide (MoS2) films are ultra-sensitive to several important environmental molecules. Here we report new findings from ab inito calculations that reveal substantially enhanced adsorption of NO and NH3 on strained monolayer MoS2 with significant impact on the properties of the adsorbates and the MoS2 layer. The magnetic moment of adsorbed NO can be tuned between 0 and 1 μB; strain also induces an electronic phase transition between half-metal and metal. Adsorption of NH3 weakens the MoS2 layer considerably, which explains the large discrepancy between the experimentally measured strength and breaking strain of MoS2 films and previous theoretical predictions. On the other hand, adsorption of NO2, CO, and CO2 is insensitive to the strain condition in the MoS2 layer. This contrasting behavior allows sensitive strain engineering of selective chemical adsorption on MoS2 with effective tuning of mechanical, electronic, and magnetic properties. These results suggest new design strategies for constructing MoS2-based ultrahigh-sensitivity nanoscale sensors and electromechanical devices.

Carbon nanotube composite sensor for structural health monitoring of bridge structures

Bridges are important infrastructures of all nations and are required for transportation of goods as well as human. A catastrophic failure can result in loss of lives and enormous financial hardship to the nation. Although various kinds of sensors are now available to monitor the health of the structures due to corrosion, they do not provide permanent and long term measurements. This paper investigates the fabrication of Carbon Nanotube (CNT) based composite sensors for corrosion detection of structures. Multi-wall CNT (MWCNT)/Nafion composite sensors were fabricated to evaluate their electrical properties for corrosion detection. The test specimens were subjected to real life corrosion experimental tests and the results confirm that the electrical resistance of the sensor electrode was dramatically changed due to corrosion.

Sensor Network Based AUV Localisation

The operation of Autonomous Underwater Vehicles (AUVs) within underwater sensor network fields provides an opportunity to reuse the network infrastructure for long baseline localisation of the AUV. Computationally efficient localisation can be accomplished using off-the-shelf hardware that is comparatively inexpensive and which could already be deployed in the environment for monitoring purposes. This paper describes the development of a particle filter based localisation system which is implemented onboard an AUV in real-time using ranging information obtained from an ad-hoc underwater sensor network. An experimental demonstration of this approach was conducted in a lake with results presented illustrating network communication and localisation performance.

Efficient selective identity-based encryption without random oracles

We construct two efficient Identity-Based Encryption (IBE) systems that admit selective-identity security reductions without random oracles in groups equipped with a bilinear map. Selective-identity secure IBE is a slightly weaker security model than the standard security model for IBE. In this model the adversary must commit ahead of time to the identity that it intends to attack, whereas in an adaptive-identity attack the adversary is allowed to choose this identity adaptively. Our first system—BB1—is based on the well studied decisional bilinear Diffie–Hellman assumption, and extends naturally to systems with hierarchical identities, or HIBE. Our second system—BB2—is based on a stronger assumption which we call the Bilinear Diffie–Hellman Inversion assumption and provides another approach to building IBE systems. Our first system, BB1, is very versatile and well suited for practical applications: the basic hierarchical construction can be efficiently secured against chosen-ciphertext attacks, and further extended to support efficient non-interactive threshold decryption, among others, all without using random oracles. Both systems, BB1 and BB2, can be modified generically to provide “full” IBE security (i.e., against adaptive-identity attacks), either using random oracles, or in the standard model at the expense of a non-polynomial but easy-to-compensate security reduction.

Tethering for Selective Synthesis of 2,2′-Biphenols : the Acetal Method

2,2'-Biphenols are a large and diverse group of compounds with exceptional properties both as ligands and bioactive agents. Traditional methods for their synthesis by oxidative dimerisation are often problematic and lead to mixtures of ortho- and para-connected regioisomers. To compound these issues, an intermolecular dimerisation strategy is often inappropriate for the synthesis of heterodimers. The ‘acetal method’ provides a solution for these problems: stepwise tethering of two monomeric phenols enables heterodimer synthesis, enforces ortho regioselectivity and allows relatively facile and selective intramolecular reactions to take place. The resulting dibenzo[1,3]dioxepines have been analysed by quantum chemical calculations to obtain information about the activation barrier for ring flip between the enantiomers. Hydrolytic removal of the dioxepine acetal unit revealed the 2,2′-biphenol target.

Ultrasensitive strain sensors made from metal-coated carbon nanofiller/epoxy composites

A set of resistance-type strain sensors has been fabricated from metal-coated carbon nanofiller (CNF)/epoxy composites. Two nanofillers, i.e., multi-walled carbon nanotubes and vapor growth carbon fibers (VGCFs) with nickel, copper and silver coatings were used. The ultrahigh strain sensitivity was observed in these novel sensors as compared to the sensors made from the CNFs without metal-coating, and conventional strain gauges. In terms of gauge factor, the sensor made of VGCFs with silver coating is estimated to be 155, which is around 80 times higher than that in a metal-foil strain gauge. The possible mechanism responsible for the high sensitivity and its dependence with the networks of the CNFs with and without metal-coating and the geometries of the CNFs were thoroughly investigated.

Sensor fault-resilient control of interior permanent-magnet synchronous motor drives

In a conventional ac motor drive using field-oriented control, a dc-link voltage, speed, and at least two current sensors are required. Hence, in the event of sensor failure, the performance of the drive system can be severely compromised. This paper presents a sensor fault-tolerant control strategy for interior permanent-magnet synchronous motor (IPMSM) drives. Three independent observers are proposed to estimate the speed, dc-link voltage, and currents of the machine. If a sensor fault is detected, the drive system isolates the faulty sensor while retaining the remaining functional ones. The signal is then acquired from the corresponding observer in order to maintain the operation of the drive system. The experimental results provided verify the effectiveness of the proposed approach.

An MMP13-selective inhibitor delays primary tumor growth and the onset of tumor-associated osteolytic lesions in experimental models of breast cancer

We investigated the effects of the matrix metalloproteinase 13 (MMP13)-selective inhibitor, 5-(4-{4-[4-(4-fluorophenyl)-1,3-oxazol-2-yl]phenoxy}phenoxy)-5-(2-methoxyethyl) pyrimidine-2,4,6(1H,3H,5H)-trione (Cmpd-1), on the primary tumor growth and breast cancer-associated bone remodeling using xenograft and syngeneic mouse models. We used human breast cancer MDA-MB-231 cells inoculated into the mammary fat pad and left ventricle of BALB/c Nu/Nu mice, respectively, and spontaneously metastasizing 4T1.2-Luc mouse mammary cells inoculated into mammary fat pad of BALB/c mice. In a prevention setting, treatment with Cmpd-1 markedly delayed the growth of primary tumors in both models, and reduced the onset and severity of osteolytic lesions in the MDA-MB-231 intracardiac model. Intervention treatment with Cmpd-1 on established MDA-MB-231 primary tumors also significantly inhibited subsequent growth. In contrast, no effects of Cmpd-1 were observed on soft organ metastatic burden following intracardiac or mammary fat pad inoculations of MDA-MB-231 and 4T1.2-Luc cells respectively. MMP13 immunostaining of clinical primary breast tumors and experimental mice tumors revealed intra-tumoral and stromal expression in most tumors, and vasculature expression in all. MMP13 was also detected in osteoblasts in clinical samples of breast-to-bone metastases. The data suggest that MMP13-selective inhibitors, which lack musculoskeletal side effects, may have therapeutic potential both in primary breast cancer and cancer-induced bone osteolysis.

A sensor fault detection and isolation method in interior permanent-magnet synchronous motor drives based on an extended Kalman filter

Interior permanent-magnet synchronous motors (IPMSMs) become attractive candidates in modern hybrid electric vehicles and industrial applications. Usually, to obtain good control performance, the electric drives of this kind of motor require one position, one dc link, and at least two current sensors. Failure of any of these sensors might lead to degraded system performance or even instability. As such, sensor fault resilient control becomes a very important issue in modern drive systems. This paper proposes a novel sensor fault detection and isolation algorithm based on an extended Kalman filter. It is robust to system random noise and efficient in real-time implementation. Moreover, the proposed algorithm is compact and can detect and isolate all the sensor faults for IPMSM drives. Thorough theoretical analysis is provided, and the effectiveness of the proposed approach is proven by extensive experimental results.