Pure 3D Research Articles

An Enhanced Collaborative Localization Method Based on Belief Propagation Aided by 3D Terrain Modelling

Navigation system performance degrades significantly in complex environments. It is important to analyze satellite visibility through 3D terrain modelling and separate the satellite signals propagated by NLOS to suppress the NLOS error. However, the traditional 3D terrain modelling visibility analysis method based on the pure terrain cover angle is only suitable for determining the visibility of GNSS satellites and may incorrectly separate LOS propagate measurement signals from members with low relative ranges and elevation angles under air–ground swarm conditions. To this end, this paper proposes a belief-propagating cooperative navigation method based on air–ground visibility analysis, which avoids mistakenly separating close-range LOS cooperative navigation signals by simultaneously considering the distances, elevation angles, and azimuths of the signal sources relative to the air–ground swarm members. The simulation shows that the cooperative navigation NLOS identification method based on air–ground visibility analysis proposed in this paper can more accurately realize the separation of NLOS signals under cooperative conditions than the traditional pure angular 3D terrain modelling visibility analysis method can, and the localization error of the members to be assisted is significantly reduced.

Pure 3D Conducting Polymer Network for an Ultra-Sensitive and Flexible Hydrogen Gas Sensor at Room Temperature

Hydrogen (H2) is considered a next-generation energy source with diverse applications across valuable social, economic, and industrial sectors, including transportation, biomedical, power generation, and space exploration. Due to its low ignition energy and wide flammable range, there is an urgent global demand for ultrasensitive, lightweight, portable, wearable, and flexible hydrogen sensors to identify early gas leaks and prevent environmental and economic implications.In this study, we present a flexible hydrogen gas sensor based on conducting polymers, namely polypyrrole (PPY) with graphene nanoparticles, synthesized by the bi-continuous microemulsion polymerization method. The one-step scalable synthetic procedure enables the design of 1D, 2D, and 3D conducting polymers and their nanocomposites with tunable morphological and electrical properties. The unique multilayered oil-to-water nature of the bi-continuous microemulsion allows the fabrication of pure mesoporous 3D conducting polymers and their composites without the addition of any cross-linkers with excellent electrical properties. The 3D pure porous polymer network acts as a monolithic conducting framework that facilitates electron and ion transport and promotes the diffusion of molecules and ions more efficiently than 1D or 2D structures. The soft and porous nature of the polymer improves the interaction and adsorption of the target gas molecules and sensing material by increasing the number of active sites.This 3D PPY_graphene flexible network synthesized by the bi-continuous microemulsion method is successfully utilized to fabricate an ultra-sensitive flexible gas sensor. The performance of the sensor can be modified based on the reactor design. The sensor exhibits a notable response to 1 ppm of H2 gas. At room temperature, the fabricated sensor displayed 14 and 20 seconds of response and recovery time, respectively. To the best of our knowledge, no study has explored the application of 3D pure conducting polymers and their nanocomposites for hydrogen gas sensors using the bi-continuous microemulsion polymerization method, yielding such exceptional sensing results. Figure 1

Capillary trapping of various nanomaterials on additively manufactured scaffolds for 3D micro-/nanofabrication

High-precision additive manufacturing technologies, such as two-photon polymerization, are mainly limited to photo-curable polymers and currently lacks the possibility to produce multimaterial components. Herein, we report a physically bottom-up assembly strategy that leverages capillary force to trap various nanomaterials and assemble them onto three-dimensional (3D) microscaffolds. This capillary-trapping strategy enables precise and uniform assembly of nanomaterials into versatile 3D microstructures with high uniformity and mass loading. Our approach applies to diverse materials irrespective of their physiochemical properties, including polymers, metals, metal oxides, and others. It can integrate at least four different material types into a single 3D microstructure in a sequential, layer-by-layer manner, opening immense possibilities for tailored functionalities on demand. Furthermore, the 3D microscaffolds are removable, facilitating the creation of pure material-based 3D microstructures. This universal 3D micro-/nanofabrication technique with various nanomaterials enables the creation of advanced miniature devices with potential applications in multifunctional microrobots and smart micromachines.

Element Regulation and Dimensional Engineering Co-Optimization of Perovskite Memristors for Synaptic Plasticity Applications.

Capitalizing on rapid carrier migration characteristics and outstanding photoelectric conversion performance, halide perovskite memristors demonstrate an exceptional resistive switching performance. However, they have consistently faced constraints due to material stability issues. This study systematically employs elemental modulation and dimension engineering to effectively control perovskite memristors with different dimensions and A-site elements. Compared to pure 3D and 2D perovskites, the quasi-2D perovskite memristor, specifically BA0.15MA0.85PbI3, is identified as the optimal choice through observations of resistive switching (HRS current < 10-5 A, ON/OFF ratio > 103, endurance cycles > 1000, and retention time > 104 s) and synaptic plasticity characteristics. Subsequently, a comprehensive investigation into various synaptic plasticity aspects, including paired-pulse facilitation (PPF), spike-variability-dependent plasticity (SVDP), spike-rate-dependent plasticity (SRDP), and spike-timing-dependent plasticity (STDP), is conducted. Practical applications, such as memory-forgetting-memory and recognition of the Modified National Institute of Standards and Technology (MNIST) database handwritten data set (accuracy rate reaching 94.8%), are explored and successfully realized. This article provides good theoretical guidance for synaptic-like simulation in perovskite memristors.

S-duality in the Cardy-like limit of the superconformal index

We evaluate the superconformal index of 4d N\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\mathcal{N} $$\\end{document} = 4 SYM with gauge algebra so(2Nc + 1) in the Cardy-like limit. We then study the relation with the results obtained for the S-dual usp(2Nc), discussing the fate of S-duality in different regions of charges. We find that S-duality is preserved thanks to a non-trivial integral identity that relates the three sphere partition functions of pure 3d Chern-Simons gauge theories.

Pure and Cobalt-Modified ZnO Nanostructures Prepared by a New Synthesis Route Applied to Environmental Remediation

Pure and cobalt-doped 3D ZnO were produced using the microwave (MW)- ultraviolet (UV)-visible (Vis) radiation-assisted hydrothermal method (MW-UV-Vis HM). Using experimental design, the effects of cobalt and UV-Vis radiation during the synthesis stage on the physicochemical properties of the materials were evaluated with different characterization techniques such as X-ray diffraction, scanning and transmission electron microscopy, diffuse reflectance, and electrochemistry. The presence of cobalt had a great influence on the reduction of charge donors in the ZnO matrix and had their photocatalytic properties improved when produced under the effect of UV-Vis radiation. The catalytic activity of the materials has been verified in important environmental remediation reactions, such as the electrochemical reduction of CO2 and the photocatalytic degradation of emerging pollutants. The results achieved in this study show competitive efficiency values for CO2 reduction (97%) and photocatalytic degradation (91%) of emerging pollutants in natural waters, illustrating the great versatility of the produced material in distinct applications.

Multi-functional molecule advancing the efficiency of pure 3D FASnI3 perovskite solar cells based on the tin tetraiodide reduction method

Based on the Tin Tetraiodide Reduction (TTR) method, high-quality 3D-FASnI3 film was obtained by using phenylhydrazine-4-sulfonic acid as the additive in the precursor solution, breaking the efficiency record of 3D FASnI3 perovskite solar cells.

Performance assessment and optimization of three-dimensional hybrid slot–effusion jet cooling configuration of an annular combustor liner

In this study, the film cooling performance of a three-dimensional (3D) hybrid slot–effusion configuration and its advantages over a baseline pure 3D slot cooling are investigated in detail using both experimental and numerical investigations. The numerical model is validated by in-house experiments conducted on a hybrid cooling configuration with a 3D slot and staggered effusion array. Infrared thermography and hot wire anemometry are used in this study to analyze the thermal and flow fields. The cooling performance of pure 3D slot and hybrid configurations is compared under identical coolant consumption. The coolant mass flow ratio (MFR) determines the cooling behavior in hybrid cooling. At low MFRs, hybrid cooling is less effective than pure 3D slot cooling. In addition, it is observed that there exists an optimal MFR where hybrid cooling outperforms 3D slot cooling. Subsequently, the effect of key design variables on the cooling performance of the hybrid configuration is studied, and they are optimized at typical combustor operating conditions using a genetic algorithm coupled to a Kriging surrogate model. The optimal configuration is experimentally tested at laboratory conditions and compared with the baseline 3D slot configuration, and it is noted that there is a significant improvement in the cooling effectiveness. Additionally, the film cooling performance of the optimized configuration at combustor representative operating conditions of maximum BR of 2 shows an enhancement of 16% in area-averaged adiabatic effectiveness and a 60% reduction in the standard deviation of local adiabatic effectiveness as compared to the baseline 3D slot cooling.

A novel design of three‐dimensional/unidirectional hybrid composites to balance in‐plane and interlaminar mechanical properties

AbstractThe working condition of the rail transit components such as bogies is complicated, so the high comprehensive performance of composite parts is desperately required. However, existing pure three‐dimensional braided or laminated composites have been unable to satisfy the cooperative demand of in‐plane and interlaminar properties. In this paper, a novel design of three‐dimensional braided/unidirectional (3D/UD) hybrid composite is proposed to balance the in‐plane (tensile, compression, bending), interlaminar (interlaminar shear, low‐speed impact) properties of the composite. The effects of different 3D/UD mixing ratio and layup sequence on the mechanical properties and damage mechanism of hybrid composites were studied by the parametric analysis of the experimental test results, and the comprehensive mechanical properties of the hybrid structure were optimized by COPRAS evaluation method. The results show that the larger the proportion of unidirectional layer, the better the mechanical property in‐plane, but the worse interlayer property. In addition, the change of layup sequence induces a complex nonlinear relationship between 3D/UD mixing ratio and mechanical properties. Combined with microscopic failure characterization results, it is found that the sandwich structure and the addition of uniformly distributed interfacial layer can improve the mechanical properties of the hybrid composite. The optimization results show that the sandwich structure hybrid composite UD6/3D/UD6 with the best balance between in‐plane and interlaminar properties was selected by COPRAS. Compared with pure 3D composites, the comprehensive mechanical properties of UD6/3D/UD6 are increased by 53.9%, which provides a reference for the structural design of hybrid composites in the future.Highlights A novel design of 3D/UD hybrid composite is proposed to balance the in‐plane and interlaminar properties. The influence regularity of 3D/UD mixing ratio and layup sequence on properties of hybrid composites were obtained. The mixing failure mechanism of interlayer and in‐plane was revealed. The optimal structure UD6/3D/UD6 under complex working conditions was obtained by COPRAS.

Mechanical Properties' Strengthening of Photosensitive 3D Resin in Lithography Technology Using Acrylated Natural Rubber.

Acrylated natural rubber (ANR) with various acrylate contents (0.0-3.5 mol%) was prepared from natural rubber as a raw material and then incorporated with commercial 3D resin to fabricate specimens using digital light processing. As a result, the utilization of ANR with 1.5 mol% acrylate content could provide the maximum improvement in stretchability and impact strength, approximately 155% and 221%, respectively, over using pure 3D resin, without significant deterioration of tensile modulus and mechanical strength. According to evidence from a scanning electron microscope, this might be due to the partial interaction between the dispersed small rubber particles and the resin matrix. Additionally, the glass-transition temperature of the 3D-printed sample shifted to a lower temperature by introducing a higher acrylate content in the ANR. Therefore, this work might offer a practical way to effectively enhance the properties of the fundamental commercial 3D resin and broaden its applications. It also makes it possible to use natural rubber as a bio-based material in light-based 3D printing.

Highly contractile 3D tissue engineered skeletal muscles from human iPSCs reveal similarities with primary myoblast-derived tissues.

Skeletal muscle research is transitioning toward 3D tissue engineered invitro models reproducing muscle's native architecture and supporting measurement of functionality. Human induced pluripotent stem cells (hiPSCs) offer high yields of cells for differentiation. It has been difficult to differentiate high-quality, pure 3D muscle tissues from hiPSCs that show contractile properties comparable to primary myoblast-derived tissues. Here, we present a transgene-free method for the generation of purified, expandable myogenic progenitors (MPs) from hiPSCs grown under feeder-free conditions. We defined a protocol with optimal hydrogel and medium conditions that allowed production of highly contractile 3D tissue engineered skeletal muscles with forces similar to primary myoblast-derived tissues. Gene expression and proteomic analysis between hiPSC-derived and primary myoblast-derived 3D tissues revealed a similar expression profile of proteins involved in myogenic differentiation and sarcomere function. The protocol should be generally applicable for the study of personalized human skeletal muscle tissue in health and disease.

An integrated network based on 2D/3D feature correlations for benign-malignant tumor classification and uncertainty estimation in digital breast tomosynthesis

Objective. Classification of benign and malignant tumors is important for the early diagnosis of breast cancer. Over the last decade, digital breast tomosynthesis (DBT) has gradually become an effective imaging modality for breast cancer diagnosis due to its ability to generate three-dimensional (3D) visualizations. However, computer-aided diagnosis (CAD) systems based on 3D images require high computational costs and time. Furthermore, there is considerable redundant information in 3D images. Most CAD systems are designed based on 2D images, which may lose the spatial depth information of tumors. In this study, we propose a 2D/3D integrated network for the diagnosis of benign and malignant breast tumors. Approach. We introduce a correlation strategy to describe feature correlations between slices in 3D volumes, corresponding to the tissue relationship and spatial depth features of tumors. The correlation strategy can be used to extract spatial features with little computational cost. In the prediction stage, 3D spatial correlation features and 2D features are both used for classification. Main results. Experimental results demonstrate that our proposed framework achieves higher accuracy and reliability than pure 2D or 3D models. Our framework has a high area under the curve of 0.88 and accuracy of 0.82. The parameter size of the feature extractor in our framework is only 35% of that of the 3D models. In reliability evaluations, our proposed model is more reliable than pure 2D or 3D models because of its effective and nonredundant features. Significance. This study successfully combines 3D spatial correlation features and 2D features for the diagnosis of benign and malignant breast tumors in DBT. In addition to high accuracy and low computational cost, our model is more reliable and can output uncertainty value. From this point of view, the proposed method has the potential to be applied in clinic.

Resolving the Ultrafast Charge Carrier Dynamics of 2D and 3D Domains within a Mixed 2D/3D Lead‐Tin Perovskite

AbstractMixed 2D/3D perovskite materials are of particular interest to the photovoltaics and light‐ emitting diode (LED) communities due to their impressive opto‐electronic properties alongside improved moisture stability compared to conventional 3D perovskite absorbers. Here, a mixed lead‐tin perovskite containing distinct, self‐assembled domains of either 3D structures or highly phase‐pure Ruddlesden–Popper 2D structures is studied. The complex energy landscape of the material is revealed with ultrafast optical transient absorption measurements. It is shown that charge transfer between these microscale domains only occurs on nanosecond timescales, consistent with the large size of the domains. Using optical pump‐terahertz probe spectroscopy, the effective charge‐carrier mobility is shown to be an intermediary between analogous pure 2D and 3D perovskites. Furthermore, detailed analysis of the free carrier recombination dynamics is presented. By combining results from a range of excitation wavelengths within a full dynamic model of the photoexcited carrier population, it is shown that the 2D domains in the film exhibit remarkably similar carrier dynamics to the 3D domains, suggesting that long‐range charge‐transport should not be impeded by the heterogeneous structure of the material.

Glass Fiber Reinforced Acrylonitrile Butadiene Styrene Composite Gears by FDM 3D Printing

Abstract3D printing of gears via fused deposition modeling (FDM) has been recently introduced as a low‐cost efficient manufacturing method. Different materials have been 3D printed and Acrylonitrile Butadiene Styrene (ABS) with excellent mechanical properties has been found to be promising. However, 3D printed ABS gears possess a high level of abrasion rate. This paper introduces a new class of ABS‐based gears reinforced by different amounts of milled E‐glass fibers and 3D printed by FDM with acceptable thermo‐mechanical properties and performance. A set of thermo‐mechanical tests is carried out to provide an insight into the influence of adding glass fibers on the glass transition temperature (Tg), hardness and teeth bending strength, teeth failure force, weight lost, abrasion resistance, mechanical wear, and performance of composite gears. The mechanical behaviors of driving and driven gears are examined in high and room temperatures with or without lubrication. Microstructure and gear profile analysis of 3D printed layers, worn surfaces, and fracture locations are also conducted by SEM images and profile projector. The newly developed glass fiber reinforced ABS gears reveal a high level of thermo‐mechanical performance in terms of hardness, mechanical strength, bending force, abrasion and wear resistance compared to pure 3D printed ABS gears.

Rethinking 3D-CNN in Hyperspectral Image Super-Resolution

Recently, CNN-based methods for hyperspectral image super-resolution (HSISR) have achieved outstanding performance. Due to the multi-band property of hyperspectral images, 3D convolutions are natural candidates for extracting spatial–spectral correlations. However, pure 3D CNN models are rare to see, since they are generally considered to be too complex, require large amounts of data to train, and run the risk of overfitting on relatively small-scale hyperspectral datasets. In this paper, we question this common notion and propose Full 3D U-Net (F3DUN), a full 3D CNN model combined with the U-Net architecture. By introducing skip connections, the model becomes deeper and utilizes multi-scale features. Extensive experiments show that F3DUN can achieve state-of-the-art performance on HSISR tasks, indicating the effectiveness of the full 3D CNN on HSISR tasks, thanks to the carefully designed architecture. To further explore the properties of the full 3D CNN model, we develop a 3D/2D mixed model, a popular kind of model prior, called Mixed U-Net (MUN) which shares a similar architecture with F3DUN. Through analysis on F3DUN and MUN, we find that 3D convolutions give the model a larger capacity; that is, the full 3D CNN model can obtain better results than the 3D/2D mixed model with the same number of parameters when it is sufficiently trained. Moreover, experimental results show that the full 3D CNN model could achieve competitive results with the 3D/2D mixed model on a small-scale dataset, suggesting that 3D CNN is less sensitive to data scaling than what people used to believe. Extensive experiments on two benchmark datasets, CAVE and Harvard, demonstrate that our proposed F3DUN exceeds state-of-the-art HSISR methods both quantitatively and qualitatively.

Exploring, Identifying, and Removing the Efficiency-Limiting Factor of Mixed-Dimensional 2D/3D Perovskite Solar Cells

ConspectusThree-dimensional (3D) halide perovskite (HP) solar cells have been thriving as promising postsilicon photovoltaic systems. However, despite the decency of efficiency, they suffer from poor stability. Partial dimensionality reduction from 3D to 2D was found to significantly meliorate the instability, thus mixed-dimensional 2D/3D HP solar cells have been expected to combine favorable durability and high efficiency. Nevertheless, their power conversion efficiency (PCE) does not live up to the expectation, hardly exceeding 19%, in sharp contrast with the ∼26% benchmark for pure 3D HP solar cells. The low PCE primarily arises from the restricted charge transport of the mixed-phasic 2D/3D HP layer. Understanding its photophysical dynamics, including its nanoscopic phase distribution and interphase carrier transfer kinetics, is essential for fathoming the underlying restriction mechanism. This Account outlines the three historical photophysical models of the mixed-phasic 2D/3D HP layer (denoted as models I, II, and III hereafter). Model I opines (i) a gradual dimensionality transition in the axial direction and (ii) a type II band alignment between 2D and 3D HP phases, hence favorably driving global carrier separation. Model II takes the view that (i) 2D HP fragments are interspersed in the 3D HP matrix with a macroscopic concentration variation in the axial direction and (ii) 2D and 3D HP phases instead form a type I band alignment. Photoexcitations would rapidly transfer from wide-band-gap 2D HPs to narrow-band-gap 3D HPs, which then serve as the charge transport network. Model II is currently the most widely accepted. We are one of the earliest groups to unveil the ultrafast interphase energy-transfer process. Recently, we further amended the photophysical model to consider also (i) an interspersing pattern of phase distribution but (ii) the 2D/3D HP heterojunction to be a p-n heterojunction with built-in potential. Anomalously, the built-in potential of the 2D/3D HP heterojunction increases upon photoexcitation. Therefore, local 3D/2D/3D misalignments would severely impede charge transport due to carrier blocking or trapping. Contrary to models I and II which hold 2D HP fragments as the culprit, model III rather suspects the 2D/3D HP interface for blunting the charge transport. This insight also rationalizes the distinct photovoltaic performances of the mixed-dimensional 2D/3D configuration and the 2D-on-3D bilayer configuration. To extinguish the detrimental 2D/3D HP interface, our group also developed an approach to alloy the multiphasic 2D/3D HP assembly into phase-pure intermediates. The accompanying challenges that are coming are also discussed.

Process of Pure Copper Fabricated by Selective Laser Melting (SLM) Technology under Moderate Laser Power with Re-Melting Strategy.

Pure copper (Cu) material, because of its high thermal conductivity, can be 3D printed to fabricate effective thermal management components. However, in the selective laser melting (SLM) process, due to copper's high optical reflectivity, Cu-based parts need to be printed using high laser power. In this study, we demonstrated 3D printing with a re-melting strategy is able to fabricate high-density and low-surface-roughness pure copper parts using only a moderate laser (350 W) power. The effect of the re-scan to initial scan speed ratio on the printing quality resulting from the re-melting strategy is discussed. The re-melting strategy is likened to a localized annealing process that promotes the recrystallization of the newly formed copper microstructures on the re-scan path. Given a hatch spacing of 0.06 mm and a powder layer thickness of 0.05 mm, Cu samples with 93.8% density and low surface roughness (Sa~22.9 μm) were produced using an optimized scan speed of 200 mm/s and a re-scanning speed of 400 mm/s, with a laser power of 350 W. Our work provides an approach to optimize the laser power for printing pure copper 3D parts with high relative density (low porosity) and low surface roughness while ensuring the lifetime stability of the part. The re-melting strategies have broad implications in 3D printing and are particularly relevant for metals with high reflectivity, such as pure copper.

Multislice input for 2D and 3D residual convolutional neural network noise reduction in CT.

Deep convolutional neural network (CNN)-based methods are increasingly used for reducing image noise in computed tomography (CT). Current attempts at CNN denoising are based on 2D or 3D CNN models with a single- or multiple-slice input. Our work aims to investigate if the multiple-slice input improves the denoising performance compared with the single-slice input and if a 3D network architecture is better than a 2D version at utilizing the multislice input. Two categories of network architectures can be used for the multislice input. First, multislice images can be stacked channel-wise as the multichannel input to a 2D CNN model. Second, multislice images can be employed as the 3D volumetric input to a 3D CNN model, in which the 3D convolution layers are adopted. We make performance comparisons among 2D CNN models with one, three, and seven input slices and two versions of 3D CNN models with seven input slices and one or three output slices. Evaluation was performed on liver CT images using three quantitative metrics with full-dose images as reference. Visual assessment was made by an experienced radiologist. When the input channels of the 2D CNN model increases from one to three to seven, a trend of improved performance was observed. Comparing the three models with the seven-slice input, the 3D CNN model with a one-slice output outperforms the other models in terms of noise texture and homogeneity in liver parenchyma as well as subjective visualization of vessels. We conclude the that multislice input is an effective strategy for improving performance for 2D deep CNN denoising models. The pure 3D CNN model tends to have a better performance than the other models in terms of continuity across axial slices, but the difference was not significant compared with the 2D CNN model with the same number of slices as the input.

FloorUSG: Indoor floorplan reconstruction by unifying 2D semantics and 3D geometry

This paper proposes a multistage floorplan reconstruction approach from RGB images and a dense 3D mesh, called FloorUSG, by combining 2D plane instances and 3D plane primitives. In primitive detection, plane instances inferred from images complement the results of traditional 3D plane detection well. And in the optimization, both the plane confidence and the geometric quality of data are considered to select the optimal subset from the candidates. Different from existing methods that rely on delicate corner detection from a planar graph or pure geometric 3D plane detection, our framework accurately recovers the location of the floorplan via 2D–3D primitive fusion. Experimental results indicate that our method has the ability to recover detailed structures of scenes of different scales and can reconstruct the floorplan from imperfect data with high robustness compared to the state-of-the-art algorithms.

Camera Pose Optimization for 3D Mapping

Digital 3D models of environments are of great value in many applications, but the algorithms that build them autonomously are computationally expensive and require a considerable amount of time to perform this task. In this work, we present an active simultaneous localisation and mapping system that optimises the pose of the sensor for the 3D reconstruction of an environment, while a 2D Rapidly-Exploring Random Tree algorithm controls the motion of the mobile platform for the ground exploration strategy. Our objective is to obtain a 3D map comparable to that obtained using a complete 3D approach in a time interval of the same order of magnitude of a 2D exploration algorithm. The optimisation is performed using a ray-tracing technique from a set of candidate poses based on an uncertainty octree built during exploration, whose values are calculated according to where they have been viewed from. The system is tested in diverse simulated environments and compared with two different exploration methods from the literature, one based on 2D and another one that considers the complete 3D space. Experiments show that combining our algorithm with a 2D exploration method, the 3D map obtained is comparable in quality to that obtained with a pure 3D exploration procedure, but demanding less time.