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Modern UAVs (unmanned aerial vehicles) equipped with video cameras can provide large-scale high-resolution video data. This poses significant challenges for structure from motion (SfM) and simultaneous localization and mapping (SLAM) algorithms, as most of them are developed for relatively small-scale and low-resolution scenes. In this paper, we present a video-based SfM method specifically designed for high-resolution large-size UAV videos. Despite the wide range of applications for SfM, performing mainstream SfM methods on such videos poses challenges due to their high computational cost. Our method consists of three main steps. Firstly, we employ a visual SLAM (VSLAM) system to efficiently extract keyframes, keypoints, initial camera poses, and sparse structures from downsampled videos. Next, we propose a novel two-step keypoint adjustment method. Instead of matching new points in the original videos, our method effectively and efficiently adjusts the existing keypoints at the original scale. Finally, we refine the poses and structures using a rotation-averaging constrained global bundle adjustment (BA) technique, incorporating the adjusted keypoints. To enrich the resources available for SLAM or SfM studies, we provide a large-size (3840 × 2160) outdoor video dataset with millimeter-level-accuracy ground control points, which supplements the current relatively low-resolution video datasets. Experiments demonstrate that, compared with other SLAM or SfM methods, our method achieves an average efficiency improvement of 100% on our collected dataset and 45% on the EuRoc dataset. Our method also demonstrates superior localization accuracy when compared with state-of-the-art SLAM or SfM methods.
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Mn-based layered oxide is extensively investigated as a promising cathode material for potassium-ion batteries due to its high theoretical capacity and natural abundance of manganese. However, the Jahn-Teller distortion caused by high-spin Mn3+ (t2g 3 eg 1 ) destabilizes the host structure and reduces the cycling stability. Here, K0.02 Na0.55 Mn0.70 Ni0.25 Zn0.05 O2 (denoted as KNMNO-Z) is reported to inhibit the Jahn-Teller effect and reduce the irreversible phase transition. Through the implementation of a Zn-doping strategy, higher Mn valence is achieved in the KNMNO-Z electrode, resulting in a reduction of Mn3+ amount and subsequently leading to an improvement in cyclic stability. Specifically, after 1000 cycles, a high retention rate of 97% is observed. Density functional theory calculations reveals that low-valence Zn2+ ions substituting the transition metal position of Mn regulated the electronic structure around the MnO bonding, thereby alleviating the anisotropic coupling between oxidized O2- and Mn4+ and improving the structural stability. K0.02 Na0.55 Mn0.70 Ni0.25 Zn0.05 O2 provided an initial discharge capacity of 57 mAh g-1 at 100 mA g-1 and a decay rate of only 0.003% per cycle, indicating that the Zn-doped strategy is effective for developing high-performance Mn-based layered oxide cathode materials in PIBs.
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Recently proposed spherical convolutional neural networks (SCNNs) have shown advantages over conventional planar CNNs on classifying spherical images. However, two factors hamper their application in an objection detection task. First, a convolution in S2 (a two-dimensional sphere in three-dimensional space) or SO(3) (three-dimensional special orthogonal group) space results in the loss of an object's location. Second, overlarge bandwidth is required to preserve a small object's information on a sphere because the S2/SO(3) convolution must be performed on the whole sphere, instead of a local image patch. In this study, we propose a novel grid-based spherical CNN (G-SCNN) for detecting objects from spherical images. According to input bandwidth, a sphere image is transformed to a conformal grid map to be the input of the S2/SO3 convolution, and an object's bounding box is scaled to cover an adequate area of the grid map. This solves the second problem. For the first problem, we utilize a planar region proposal network (RPN) with a data augmentation strategy that increases rotation invariance. We have also created a dataset including 600 street view panoramic images captured from a vehicle-borne panoramic camera. The dataset contains 5636 objects of interest annotated with class and bounding box and is named as WHU (Wuhan University) panoramic dataset. Results on the dataset proved our grid-based method is extremely better than the original SCNN in detecting objects from spherical images, and it outperformed several mainstream object detection networks, such as Faster R-CNN and SSD.
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We propose utilizing a rigorous registration model and a skyline-based method for automatic registration of LiDAR points and a sequence of panoramic/fish-eye images in a mobile mapping system (MMS). This method can automatically optimize original registration parameters and avoid the use of manual interventions in control point-based registration methods. First, the rigorous registration model between the LiDAR points and the panoramic/fish-eye image was built. Second, skyline pixels from panoramic/fish-eye images and skyline points from the MMS’s LiDAR points were extracted, relying on the difference in the pixel values and the registration model, respectively. Third, a brute force optimization method was used to search for optimal matching parameters between skyline pixels and skyline points. In the experiments, the original registration method and the control point registration method were used to compare the accuracy of our method with a sequence of panoramic/fish-eye images. The result showed: (1) the panoramic/fish-eye image registration model is effective and can achieve high-precision registration of the image and the MMS’s LiDAR points; (2) the skyline-based registration method can automatically optimize the initial attitude parameters, realizing a high-precision registration of a panoramic/fish-eye image and the MMS’s LiDAR points; and (3) the attitude correction values of the sequences of panoramic/fish-eye images are different, and the values must be solved one by one.
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Layered transition-metal oxides (Li[NixMnyCoz]O2, NMC, or NMCxyz) due to their poor stability when cycled at a high operating voltage (>4.5 V) have limited their practical applications in industry. Earlier researches have identified Mn(II)-dissolution and some parasitic reactions between NMC surface and electrolyte, especially when NMC is charged to a high potential, as primarily factors responsible for the fading. In our previous work, we have achieved a capacity of NMC active material close to theoretical value and optimized its cycling performance by a depolarized carbon nanotubes (CNTs) network and an unique "pre-lithiation process" that generates an in situ organic coating (â¼40 nm) to prevent Mn(II) dissolution and minimize the parasitic reactions. Unfortunately, this organic coating is not durable enough during a long-term cycling when the cathode operates at a high potential (>4.5 V). This work attempts to improve the surface protection of the NMC532 particles by applying an active inorganic coating consisting of nanosized- and crystal-orientated LiFePO4 (LFP) (about 50 nm, exposed (010) face) to generate a core-shell nanostructure of Li(NixMnyCoz)O2@LiFePO4. Transmission electron microscopy (TEM) and etching X-ray photoelectron spectroscopy have confirmed an intimate contact coating (about 50 nm) between the original structure of NMC and LFP single-particle with atomic interdiffusion at the core-shell interface, and an array of interconnected aligned Li+ tunnels are observed at the interface by cross-sectional high-resolution TEM, which were formed by ball-milling and then strictly controlling the temperature below 100 °C. Batteries based on this modified NMC cathode material show a high reversible capacity when cycled between 3.0 and 4.6 V during a long-term cycling.
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For multi-sensor integrated systems, such as the mobile mapping system (MMS), data fusion at sensor-level, i.e., the 2D-3D registration between an optical camera and LiDAR, is a prerequisite for higher level fusion and further applications. This paper proposes a line-based registration method for panoramic images and a LiDAR point cloud collected by a MMS. We first introduce the system configuration and specification, including the coordinate systems of the MMS, the 3D LiDAR scanners, and the two panoramic camera models. We then establish the line-based transformation model for the panoramic camera. Finally, the proposed registration method is evaluated for two types of camera models by visual inspection and quantitative comparison. The results demonstrate that the line-based registration method can significantly improve the alignment of the panoramic image and the LiDAR datasets under either the ideal spherical or the rigorous panoramic camera model, with the latter being more reliable.
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Transition metal oxide materials Li(NixMnyCoz)O2 (NMC) based on layered structures are expected to replace LiFePO4 in automotive Li-ion batteries because of their higher specific capacity and operating potential. However, the actual usable capacity is much lower than the promised theoretical value [Uchaker, E.; Cao, G. Nano Today 2014, 9, 499-524; Tarascon, J.-M.; Armand, M. Nature 2001, 414, 359-367], in addition to the often poor cycling performance and the first-cycle Coulombic efficiency, for which Mn(II)-dissolution, its immobilization in solid electrolyte interface (SEI), oxidation of electrolytes by Ni, and other parasitic process thereat have been held responsible [Zhan, C., et al. Nat. Commun. 2013, 4, 2437; Wang, L., et al. J. Solid State Electrochem. 2009, 13, 1157-1164; Lin, F., et al. Nat. Commun. 2014, 5, 4529]. Previously, we reported a composite Li(Ni0.5Mn0.3Co0.2)O2 (NMC532) depolarized by the embedded carbon nanotube (CNT) and achieved capacity close to the theoretical limit [Wu, Z., et al. Nano. Lett. 2014, 14, 4700-4706]; unfortunately, this high capacity failed to be maintained in long-term cycling due to the degrading contacts between the active ingredient and CNT network. On the basis of that NMC532/CNT composite, the present work proposes a unique "prelithiation process", which brought the cathode to low potentials before regular cycling and led to an interphase that is normally formed only on anode surfaces. The complete coverage of cathode surface by this â¼40 nm thick interphase effectively prevented Mn(II) dissolution and minimized the side reactions of Ni, Co, and Mn at the NMC interface during the subsequent cycling process. More importantly, such a "prelithiation" process activated a structure containing two Li layers near the surface of NMC532 particles, as verified by XRD and first principle calculation. Hence, a new cathode material of both high capacity with depolarized structure and excellent cycling performance was generated. This new structure can be incorporated in essentially all the NMC-based layered cathode materials, providing us with an effective tool to tailor-design future new cathode materials for lithium batteries.
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The hexanitratolanthanate anion (La(NO(3))(6)(3-)) is an interesting symmetric anion suitable to construct the component of water-free rare-earth-metal ionic liquids. The syntheses and structural characterization of eleven lanthanum nitrate complexes, [C(n)mim](3)[La(NO(3))(6)] (n=1, 2, 4, 6, 8, 12, 14, 16, 18), including 1,3-dimethylimidazolium hexanitratolanthanate ([C(1)mim](3)[La(NO(3))(6)], 1), 1-ethyl-3-methylimidazolium hexanitratolanthanate ([C(2)mim](3)[La(NO(3))(6)], 2), 1-butyl-3-methylimidazolium hexanitratolanthanate ([C(4)mim](3)[La(NO(3))(6)], 3), 1-isobutyl-3-methylimidazolium hexanetratolanthanate ([isoC(4)mim](3)[La(NO(3))(6)], 4), 1-methyl-3-(3'-methylbutyl)imidazolium hexanitratolanthanate ([MC(4)mim](3)[La(NO(3))(6)], 5), 1-hexyl-3-methylimidazolium hexanitratolanthanate ([C(6)mim](3)[La(NO(3))(6)], 6), 1-methyl-3-octylimidazolium hexanitratolanthanate ([C(8)mim](3)[La(NO(3))(6)], 7), 1-dodecyl-3-methylimidazolium hexanitratolanthanate ([C(12)mim](3)[La(NO(3))(6)], 8), 1-methyl-3-tetradecylimidazolium hexanitratolanthanate ([C(14)mim](3)[La-(NO(3))(6)], 9), 1-hexadecyl-3-methylimid-azolium hexanitratolanthanum ([C(16)dmim](3)[La(NO(3))(6)], 10), and 1-methyl-3-octadecylimidazolium hexanitratolanthanate ([C(18)mim](3)[La(NO(3))(6)], 11) are reported. All new compounds were characterized by (1)H and (13)C NMR, and IR spectroscopy as well as elemental analysis. The crystal structure of compound 1 was determined by using single-crystal X-ray diffraction, giving the following crystallographic information: monoclinic; P2(1)/c; a=15.3170 (3), b=14.2340 (2), c=13.8954(2) Å; ß=94.3453(15)°, V=3020.80(9) Å(3), Z=4, ρ=1.764 g cm(-3). The coordination polyhedron around the lanthanum ion is rationalized by six nitrate anions with twelve oxygen atoms. No hydrogen-bonding network or water molecule was found in 1. The thermodynamic stability of the new complexes was investigated by using thermogravimetric analysis (TGA). The water-free hexanitratolanthanate ionic liquids are thermal and moisture stable. Four complexes, namely complexes 8-11, were found to be ionic liquid crystals by differential scanning calorimetry (DSC) and polarizing optical microscopy (POM). They all present smectic A liquid-crystalline phase.
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Accurate localization of moving sensors is essential for many fields, such as robot navigation and urban mapping. In this paper, we present a framework for GPS-supported visual Simultaneous Localization and Mapping with Bundle Adjustment (BA-SLAM) using a rigorous sensor model in a panoramic camera. The rigorous model does not cause system errors, thus representing an improvement over the widely used ideal sensor model. The proposed SLAM does not require additional restrictions, such as loop closing, or additional sensors, such as expensive inertial measurement units. In this paper, the problems of the ideal sensor model for a panoramic camera are analysed, and a rigorous sensor model is established. GPS data are then introduced for global optimization and georeferencing. Using the rigorous sensor model with the geometric observation equations of BA, a GPS-supported BA-SLAM approach that combines ray observations and GPS observations is then established. Finally, our method is applied to a set of vehicle-borne panoramic images captured from a campus environment, and several ground control points (GCP) are used to check the localization accuracy. The results demonstrated that our method can reach an accuracy of several centimetres.
Assuntos
Monitoramento Ambiental/instrumentação , Monitoramento Ambiental/métodos , Tecnologia de Sensoriamento Remoto/instrumentação , Algoritmos , Desenho de Equipamento , Sistemas de Informação Geográfica , Reprodutibilidade dos Testes , RobóticaRESUMO
Hydrophobic/superhydrophobic materials with intrinsic water repellence are highly desirable in engineering fields including anti-icing in aerocrafts, antidrag and anticorrosion in ships, and antifog and self-cleaning in optical lenses, screen, mirrors, and windows. However, superhydrophobic material should have small surface energy (SE) and a micro/nanosurface structure which can reduce solid-liquid contact significantly. The low SE is generally found in organic materials with inferior mechanical properties that is undesirable in engineering. Intriguingly, previous theoretical calculations have predicted a negative SE for θ-alumina (θ-Al2O3), which inspires us to use it as a superhydrophobic material. Here, we report the experimental evidence of the small/negative SE of θ-Al2O3 and a θ-Al2O3-based superhydrophobic coating prepared by one-step scalable plasma arcing oxidation. The superhydrophobic coating has complete ceramic and desired micro/nanostructure and therefore exhibits excellent aging resistance, wear resistance, corrosion resistance, high-temperature tolerance, and burning resistance. Owing to the rarity of the small/negative SE in inorganic materials, the concept to reduce SE by θ-Al2O3 may foster a blowout to develop robust superhydrophobicity by complete inorganic materials.
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Transition metal oxide materials Li(NixMnyCoz)O2 (NMCxyz) based on layered structure are potential cathode candidates for automotive Li-ion batteries because of their high specific capacities and operating potentials. However, the actual usable capacity, cycling stability, and first-cycle Coulombic efficiency remain far from practical. Previously, we reported a combined strategy consisting of depolarization with embedded carbon nanotube (CNT) and activation through pre-lithiation of the NMC host, which significantly improved the reversible capacity and cycling stability of NMC532-based material. In the present work we attempt to understand how pre-lithiation leads to these improvements on an atomic level with experimental investigation and ab initio calculations. By lithiating a series of NMC materials with varying chemical compositions prepared via a conventional approach, we identified the Ni in the NMC lattice as the component responsible for accommodating a double-layered Li structure. Specifically, much better improvements in the cycling stability and capacity can be achieved with the NMC lattices populated with Ni(3+) than those populated with only Ni(2+). Using the XRD we also found that the emergence of a double-layer Li structure is not only reversible during the pre-lithiation and the following delithiation, but also stable against elevated temperatures up to 320 °C. These new findings regarding the mechanism of pre-lithiation as well as how it affects the reversibility and stability of NMC-based cathode materials prepared by the conventional slurry approach will promote the possibility of their application in the future battery industry.
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Five hexanitratoneodymate-based rare earth complexes () were synthesized using a straightforward method. Purple plate crystals of were isolated and the crystal structure was determined by single-crystal X-ray diffraction with respect to the coordination mode of the nitrate anion to the central Nd(iii) ion. (: monoclinic system P21/c, a = 15.9460(3) Å, b = 10.2457(6) Å, c = 33.323(3) Å, ß = 91.8108(17)°, V = 3109.11(11) Å(3), Z = 4). The central Nd(iii) ion is surrounded by six bidentate nitrate ligands, with a major trend towards high symmetry of the [Nd(NO3)6](3-) anion as an icosahedron. Thermal properties were determined from differential scanning calorimetry (DSC) combined with thermogravimetric analysis (TGA) tests. Complexes are found to be room temperature liquids, and their excitation and emission spectra were recorded. These complexes exhibit intense near-infrared (NIR) luminescence emission, which originates from interconfigurational f-f transitions (4)F3/2â(4)IJ multiplet (J = 9/2-13/2). These liquid Nd(iii) complexes are of interest as potential NIR luminescent soft materials with high thermal stability.