Multi-Sensor-Assisted Low-Cost Indoor Non-Visual Semantic Map Construction and Localization for Modern Vehicles.

With the transformation and development of the automotive industry, low-cost and seamless indoor and outdoor positioning has become a research hotspot for modern vehicles equipped with in-vehicle infotainment systems, Internet of Vehicles, or other intelligent systems (such as Telematics Box, Autopilot, etc.). This paper analyzes modern vehicles in different configurations and proposes a low-cost, versatile indoor non-visual semantic mapping and localization solution based on low-cost sensors. Firstly, the sliding window-based semantic landmark detection method is designed to identify non-visual semantic landmarks (e.g., entrance/exit, ramp entrance/exit, road node). Then, we construct an indoor non-visual semantic map that includes the vehicle trajectory waypoints, non-visual semantic landmarks, and Wi-Fi fingerprints of RSS features. Furthermore, to estimate the position of modern vehicles in the constructed semantic maps, we proposed a graph-optimized localization method based on landmark matching that exploits the correlation between non-visual semantic landmarks. Finally, field experiments are conducted in two shopping mall scenes with different underground parking layouts to verify the proposed non-visual semantic mapping and localization method. The results show that the proposed method achieves a high accuracy of 98.1% in non-visual semantic landmark detection and a low localization error of 1.31 m.

Crowdsourcing-Based Indoor Semantic Map Construction and Localization Using Graph Optimization.

The advancement of smartphones with multiple built-in sensors facilitates the development of crowdsourcing-based indoor map construction and localization. This paper proposes a crowdsourcing-based indoor semantic map construction and localization method using graph optimization. Using waypoints, semantic landmarks, and Wi-Fi landmarks as nodes and the relevance between waypoints and landmarks (i.e., waypoint-waypoint, waypoint-semantic, waypoint-Wi-Fi, semantic-semantic, and Wi-Fi-Wi-Fi) as edges, the optimization graph is constructed. Initializing the venue map is the single-track semantic map with the highest quality, as determined by a proposed map quality evaluation function. The aligned venue and candidate maps are optimized while satisfying the constraints, with the candidate map exhibiting the highest degree of similarity to the venue map. The lightweight venue map is then updated in terms of waypoint and landmark attributes, as well as the relationship between waypoints and landmarks. To determine a pedestrian's location on a venue map, similarities between a local map and a venue map are evaluated. Experiments conducted in an office building and shopping mall scenes demonstrate that crowdsourcing-based venue maps are superior to single-track semantic maps. Additionally, the landmark matching-based localization method can achieve a mean localization error of less than 0.5 m on the venue map, compared to 0.6 m in a single-track semantic map.

Nickel sulfide nanoworm network architecture as a binder-free high-performance non-enzymatic glucose sensor.

Nickel sulfide nanoworm (Ni3S2 NW) network architecture was directly grown on the poly (3,4-ethylenedioxythiophene)-reduced graphene oxide hybrid films (PEDOT-rGO HFs) modified on glassy carbon electrode (GCE), acting as a binder-free sensor for high-performance non-enzymatic glucose monitoring. The sensor exhibited the satisfactory sensitivity (2123 µA mM-1 cm-2), wide linear range (15~9105 µM), low detection limit (0.48 µM), and rapid response time (< 1.5 s) at a potential of 0.5 V (vs. SCE) in 0.1 M NaOH and possessed good selectivity, reproducibility, and stability. The enhanced electrocatalytic activity of the sensor towards glucose oxidation was attributed to the particular morphology, satisfying hydrophilic nature, strong combination between Ni3S2 NWs, PEDOT-rGO, and bare GCE. Moreover, it can be used for assaying glucose in human serum samples without dilution, indicating potential for clinical diagnostic applications. Graphical abstract Nickel sulfide nanoworms (Ni3S2 NWs)/poly (3,4-ethylenedioxythiophene)-reduced graphene oxide hybrid films (PEDOT-rGO HFs) were used to construct a binder-free high-performance non-enzymatic glucose sensor with satisfactory sensitivity, wide linear range, low detection limit, good selectivity, amazing reproducibility, and stability.

An Enhanced Pedestrian Visual-Inertial SLAM System Aided with Vanishing Point in Indoor Environments.

The visual-inertial simultaneous localization and mapping (SLAM) is a feasible indoor positioning system that combines the visual SLAM with inertial navigation. There are accumulated drift errors in inertial navigation due to the state propagation and the bias of the inertial measurement unit (IMU) sensor. The visual-inertial SLAM can correct the drift errors via loop detection and local pose optimization. However, if the trajectory is not a closed loop, the drift error might not be significantly reduced. This paper presents a novel pedestrian dead reckoning (PDR)-aided visual-inertial SLAM, taking advantage of the enhanced vanishing point (VP) observation. The VP is integrated into the visual-inertial SLAM as an external observation without drift error to correct the system drift error. Additionally, the estimated trajectory's scale is affected by the IMU measurement errors in visual-inertial SLAM. Pedestrian dead reckoning (PDR) velocity is employed to constrain the double integration result of acceleration measurement from the IMU. Furthermore, to enhance the proposed system's robustness and the positioning accuracy, the local optimization based on the sliding window and the global optimization based on the segmentation window are proposed. A series of experiments are conducted using the public ADVIO dataset and a self-collected dataset to compare the proposed system with the visual-inertial SLAM. Finally, the results demonstrate that the proposed optimization method can effectively correct the accumulated drift error in the proposed visual-inertial SLAM system.

Graphitic Carbon Nitride (g-C3N4) Nanosheets/Graphene Composites: In Situ Synthesis and Enhanced Photocatalytic Performance.

A facile In Situ growth method was presented here for the preparation of graphitic carbon nitride (g-C3N4)/graphene composites, in which the direct growth and deposition of g-C3N4 nanosheets from organic N and C sources on the graphene surfaces was achieved to form the 3D contacted structure. The resulting 3D architecture possessed multilevel porous structure and efficient g-C3N4/graphene interfaces, which facilitated the fast electron transfer at the interfaces. Photoluminescence spectra showed that the recombination of photogenerated electrons and holes in the g-C3N4/graphene composites was greatly inhibited by the introduction of graphene, indicating the more efficient separation of electrons and hole in the g-C3N4/graphene composites than in pure g-C3N4. The catalytic activity of g-C3N4/graphene composite photocatalyst was enhanced by over two fold compared to pure g-C3N4 for removal of Rhodamine B under simulated sun light irradiation. This work indicates that the metal-free g-C3N4/graphene composite photocatalyst is a promising nanomaterial for further applications in water treatment.

Study on Experiment and Simulation of Shear Force on Membrane with Dynamic Cross-Flow for Lignin in Black Liquor.

To address the problem of lignin membrane fouling caused by dynamic cross-flow in the process of retaining and concentrating the black liquor byproduct of papermaking, this paper uses three different rotating structures (vane, disk and propeller) to increase the surface shear force and filtration flux of the membrane. In this paper, under different rotating speeds and different transmembrane pressure differences, numerical simulations were conducted on the shear forces generated by the three structures and the retention process on the surface of the membrane. The variation laws were also studied and compared. Under the same filtration conditions, the vane structure demonstrates better results than the propeller and disk structures in terms of increasing filtration flux. Based on the result, the vane shear force was simulated in terms of changing the particle deposition, and compared with vane rotating speeds of 100-700 r/min, the surface particle deposition of the membrane was significantly reduced at a rotating speed of 800 r/min. Finally, the numerical simulation results were experimentally validated to ensure the accuracy of the simulation. The findings provide a theoretical basis and practical value for solving the problem of lignin membrane fouling caused by dynamic cross-flow in the process of retaining and concentrating the black liquor byproduct of papermaking.

A survey of path planning of industrial robots based on rapidly exploring random trees.

Path planning is an essential part of robot intelligence. In this paper, we summarize the characteristics of path planning of industrial robots. And owing to the probabilistic completeness, we review the rapidly-exploring random tree (RRT) algorithm which is widely used in the path planning of industrial robots. Aiming at the shortcomings of the RRT algorithm, this paper investigates the RRT algorithm for path planning of industrial robots in order to improve its intelligence. Finally, the future development direction of the RRT algorithm for path planning of industrial robots is proposed. The study results have particularly guided significance for the development of the path planning of industrial robots and the applicability and practicability of the RRT algorithm.

Inverse Kinematics Solution of 6-DOF Manipulator Based on Multi-Objective Full-Parameter Optimization PSO Algorithm.

A multi-objective full-parameter optimization particle swarm optimization (MOFOPSO) algorithm is proposed in this paper to overcome the drawbacks of poor accuracy, low efficiency, and instability of the existing algorithms in the inverse kinematics(IK) solution of the manipulator. In designing the multi-objective function, the proposed algorithm considers the factors such as position, posture, and joint. To improve PSO, the proposed algorithm comprehensively analyzes all factors affecting the global and local searching abilities. Based on this, the initial population is designed following the localized uniform distribution method. Meanwhile, the inertia weight, asynchronous learning factor, and time factor are respectively designed by introducing the iteration factor. Finally, this paper tests the performance of MOFOPSO with three typical functions to obtain a better inverse kinematics solution of the 6-DOF manipulator. Also, six other algorithms are taken for performance comparison. The experimental results indicate that the proposed method not only ensures the stability of the manipulator but also achieves high accuracy and efficiency in solving the inverse kinematics of the 6-DOF manipulator.

Porous Nanofibers Formed by Heterogeneous Growth of ZnO/Ag Particles and the Enhanced Photocatalysis.

Porous ZnO/Ag nanofibers with unique multi-interface contact structures have been synthesized by an electrospinning method. The composite nanofibers with the length of several hundred micrometers are composed of uniformly distributed ZnO and Ag nanoparticles in the size range 10~30 nm. Notably, a heterogeneous growth in the interface of ZnO and Ag particles occurs. The MO degradation rate of ZnO/Ag nanofibers with Ag content of 18 wt.% is 100% in 10 min under UV-vis irradiation and that of ZnO/Ag nanofibers with Ag content of 15 wt.% is 92% in 40 min under simulated day light, which is two times that of the pure ZnO. It is attributed to a special structure that improves the generation and separation efficiency of the photo-generated charges by the expansion of the absorption edges, the utilization efficiency of the surface plasmon resonance (SPR) oscillations of Ag, and the effective transferring of electrons from ZnO through the heterogeneous-growth interface. No obvious loss of the photocatalytic activity is observed after five cycles, indicating the excellent photostability of ZnO/Ag nanofibers. The work sheds light on the structure design of highperformance composite photocatalysts.

Cr-Doped ZnO Nanoparticles: Synthesis, Characterization, Adsorption Property, and Recyclability.

In this paper, a mild solvothermal method has been employed to successfully synthesize a series of Cr-doped ZnO nanoparticles (NPs) with different Cr(3+) contents, which is a kind of novel and high-efficiency absorbent for the removal of acid dye methyl orange (MO) from aqueous solution. The as-prepared products were characterized by transmission electron microscopy (TEM), scanning electron microscopy (SEM), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), Fourier transform infrared spectroscopy (FT-IR), Brunauer, Emmet, and Teller (BET), and Zeta potential measurements. In accordance with the adsorption capacity of the products, the obtained optimal Cr/Zn molar ratio is 6%. The adsorption process of MO on Cr-doped ZnO was investigated by kinetics, thermodynamics, and isotherm technologies, which, respectively, indicated that the adsorption was fast (adsorption reached equilibrium in 2 h) and followed a pseudo-second-order model, that the adsorption process was spontaneous and endothermic, and that it agreed well with the Langmuir isotherm with a maximum adsorption capacity of 310.56 mg g(-1). Moreover, a reasonable mechanism was proposed to elucidate the reasons for their adsorption behavior. In addition, a simple and low-cost chemical method was developed to separate and recycle ZnO and MO from the used adsorbent, effectively avoiding the secondary pollution. This work can not only describe efficient experimental approaches for obtaining novel adsorbents and recycling them but also offer valuable clues for the preparation and property study of other semiconductor adsorbents.