Mesh Map Research Articles

Real-Time LiDAR–Inertial Simultaneous Localization and Mesh Reconstruction

In this paper, a novel LiDAR–inertial-based Simultaneous Localization and Mesh Reconstruction (LI-SLAMesh) system is proposed, which can achieve fast and robust pose tracking and online mesh reconstruction in an outdoor environment. The LI-SLAMesh system consists of two components, including LiDAR–inertial odometry and a Truncated Signed Distance Field (TSDF) free online reconstruction module. Firstly, to reduce the odometry drift errors we use scan-to-map matching, and inter-frame inertial information is used to generate prior relative pose estimation for later LiDAR-dominated optimization. Then, based on the motivation that the unevenly distributed residual terms tend to degrade the nonlinear optimizer, a novel residual density-driven Gauss–Newton method is proposed to obtain the optimal pose estimation. Secondly, to achieve fast and accurate 3D reconstruction, compared with TSDF-based mapping mechanism, a more compact map representation is proposed, which only maintains the occupied voxels and computes the vertices’ SDF values of each occupied voxels using an iterative Implicit Moving Least Squares (IMLS) algorithm. Then, marching cube is performed on the voxels and a dense mesh map is generated online. Extensive experiments are conducted on public datasets. The experimental results demonstrate that our method can achieve significant localization and online reconstruction performance improvements. The source code will be made public for the benefit of the robotic community.

PHOTOGRAMMETRIC MODEL OPTIMIZATION IN DIGITALIZATION OF ARCHITECTURAL HERITAGE: YEDIKULE FORTRESS

Abstract. The idea of "digitalization of architectural heritage" has recently gained prominence to represent architectural and historical assets. With all these potentials, this study aims to create optimized models that can be used in serious gaming environments by presenting a method of photogrammetry. As a case study, Yedikule Fortress and its surroundings, which have a multi-layered structure that includes many cultural aspects such as Byzantine, Ottoman, and Republican periods in the historical process, have been studied within the scope of digitizing the architectural heritage to create an optimized model for gaming environments. The study was methodologically constructed in three phases: Photogrammetry, polygon modeling, and low poly/high poly baking process. The fortress and its surroundings are modeled using a high-detail point cloud and a high-poly mesh using aerial photogrammetry. The high-poly model was taken as a reference and transferred into a low-poly model as a mesh map, texture, and light characteristics. This allowed the high poly model to operate more efficiently and effectively in game engines. As a result, the study created a detailed and optimized model for the game engines to produce serious games specific to light and texture data, to be used on devices that support mixed reality (MR) technologies.

Comparison of Point Cloud Registration Algorithms for Mixed-Reality Cross-Device Global Localization

State-of-the-art approaches for localization and mapping are based on local features in images. Along with these features, modern augmented and mixed-reality devices enable building a mesh of the surrounding space. Using this mesh map, we can solve the problem of cross-device localization. This approach is independent of the type of feature descriptors and SLAM used onboard the AR/MR device. The mesh could be reduced to the point cloud that only takes vertices. We analyzed and compared different point cloud registration methods applicable to the problem. In addition, we proposed a new pipeline Feature Inliers Graph Registration Approach (FIGRA) for the co-localization of AR/MR devices using point clouds. The comparative analysis of Go-ICP, Bayesian-ICP, FGR, Teaser++, and FIGRA shows that feature-based methods are more robust and faster than ICP-based methods. Through an in-depth comparison of the feature-based methods with the usual fast point feature histogram and the new weighted height image descriptor, we found that FIGRA has a better performance due to its effective graph-theoretic base. The proposed pipeline allows one to match point clouds in complex real scenarios with low overlap and sparse point density.

Efficient two-dimension particle element method of interior ballistic two-phase flow

Reducing the calculation cost is of great importance as the demand for interior ballistic calculation is increasing. The key factor of interior ballistic simulation is the quest to develop a more efficient method. In this paper, an efficient two-dimension particle element method (PEM) is proposed to simulate the detailed multidimensional flow of the gas and propellant particle in the chamber. Firstly, several real particles are packed as the particle element to reduce the calculation of the solid phase. In particular, the particle element matrix is established to describe the distribution of particle parameters. Secondly, the particle element boundary is adjusted according to the particle’s movement to reduce the computational cost of grid generation. Besides, the dynamic self-adapting mesh map method is adopted to realise the coupling computation between gas phase and the particle element. The application of a standard virtual gun as a standard benchmark for interior ballistic codes is used to validate the accuracy and reliability with 1.68% error. The particle element model accurately describes the distribution of flow field in the chamber. Compared with the two-fluid method, the PEM significantly improves the computational efficiency by 21.7%. The PEM may be promising for the rapid simulation of two-phase flow in interior ballistic.

The Mesh Tools Package – Introducing Annotated 3D Triangle Maps in ROS

Triangle mesh maps for robotic applications are becoming increasingly popular, but are not yet effectively supported in the Robot Operating System (ROS). We introduce the Mesh Tools package consisting of message definitions, RViz plugins and tools, as well as a persistence layer. These tools make annotated triangle maps available in ROS and allow to publish, edit and inspect such maps within the existing ROS software stack. The persistence layer efficiently loads and stores large mesh maps. The proposed plugins and tools enable the visualization and validation of the complete layered map and associated properties to allow fluid interaction. We demonstrate the seamless integration of our tools in two application areas as a proof-of-concept: Labeling of triangle clusters for semantic mapping and robot navigation on triangle meshes in rough terrain outdoor environments by integrating our tools into an existing navigation stack.

Localization by Segmented Camera Images and Mesh Map with Semantic Information

Differ from extracting feature description such as SIFT and SURF, semantic segmentation has strong robustness to optical changes such as cross-seasonal and day-night changes. In this paper, we propose advanced visual localization method using semantic segmented images and a mesh map with semantic information made from annotated LiDAR scan data and have solved the problems of previous study. In localization phase, we use traditional Monte-Carlo Localization and calculate likelihood by comparing segmented image from on-board camera and an image of the mesh map landscape as seen from a possible predicted location. This method achieved practical localization accuracy with keeping the benefit of semantic segmentation. A source code used in this experiment is available at following github page. github.com/amslabtech/semantic mesh localization

Robotic Path Planning Based on a Triangular Mesh Map

Aiming at the problem of robot path planning in complex maps, an algorithm of robot path planning based on triangular grid graph is proposed. Firstly, a weighted undirected loop graph and a feasible domain of nodes are obtained by discretizing the triangular mesh map. Next, the Dijkstra search algorithm is applied to find the feasible shortest path from an initial to a final configuration. Finally, The Douglas-Peucker algorithm is applied to remove duplicate and redundant nodes in the feasible path, and the waypoint are extracted. The final path is a curve that is obtained by connecting the several extracted waypoint. The proposed algorithm is tested for various maps. Compared with probabilistic roadmap method, the experimental results show that the proposed method can overcome the shortcomings of the random sampling method. Furthermore, the experimental result of triangular mesh map method used in two labyrinth maps show that the triangular mesh map method can solve the robot path planning problem in complex map very well, and it is an excellent algorithm for robot path planning.

Moving object removal and surface mesh mapping for path planning on 3D terrain

ABSTRACT This paper proposes a method of moving object removal and map building for path planning on 3D terrain. Our method introduces a map representation named surface mesh maps, which is built from 3D LIDAR points using graph-based SLAM with moving object removal and polygon mesh reconstruction. We need moving object removal since moving objects, such as pedestrians, are included in raw maps built by SLAM in dynamic environments. For path planning, it is desirable that only stationary (static) objects remain in the maps. Occupancy voxel filtering can be used to remove moving objects. Stationary objects have high occupancy probability, and moving objects have low occupancy probability. However, due to shallow incidence of the LIDAR beams in 3D space, it is difficult to determine the correct probability of occupancy. Hence, we improve moving object removal using a new inverse measurement model with incident angles and a two-pass scheme to properly calculate the occupancy probability. In addition, we propose a path planning method using a graph search and the graph structures of the surface mesh maps. Path costs are given to the nodes and the arcs of the graph since path planning on 3D terrain requires an appropriate cost calculation. We introduce node costs and arc costs based on slopes, roughness, height differences, and travel distances. Path planning is performed by a graph search using the costs and graph pruning using collision detection and mesh boundary detection. The main contribution of our method is to combine SLAM with moving object removal and a graph search for path planning on large-scale 3D terrain. We conducted experiments by traveling over 5 km in outdoor dynamic environments. The results showed that the proposed method is capable of moving object removal and surface mesh mapping for path planning on 3D terrain.

RECREATING CULTURAL HERITAGE ENVIRONMENTS FOR VR USING PHOTOGRAMMETRY

Abstract. In this paper, we propose a workflow for recreating places of cultural heritage in Virtual Reality (VR) using structure from motion (SfM) photogrammetry. The unique texture of heritage places makes them ideal for full photogrammetric capture. An optimized model is created from the photogrammetric data so that it is small enough to render in a real-time environment. The optimized model, combined with mesh maps (texture maps, normal maps, etc.) looks like the original high detail model. The capture of a whole space makes it possible to create a VR experience with six degrees of freedom (6DoF) that allows the user to explore the historic place. Creating these experiences can bring people to cultural heritage that is either endangered or too remote for some people to access. The workflow described in this paper will be demonstrated with the case study of Myin-pya-gu, an 11th century temple in Bagan, Myanmar.

Surface Mesh Map Building and Path Planning for 3D Terrain

Surface Mesh Map Building and Path Planning for 3D Terrain

Mapping the relative risk of surface water acidification based on cumulative acid deposition over the past 25 years in Japan

Sensitivity maps of atmospheric acid deposition in Japan have not been updated in 20 years. Here, we propose new relative risk maps of surface water acidification in forests based on a weighted overlay of cumulative potential acid deposition (CPAD) simulated for a 25-year period (1981–2005), including the sensitivities of soil and bedrock to acidification. We assumed that relative acidification risk is high in areas that exhibit high sensitivities of soil and bedrock to acid and have received a large amount of cumulative acid deposition over the past several decades. We aggregated fine soil and bedrock maps into a 20-km mesh for overlay onto an 80-km mesh map of CPAD by considering their spatial structures in Japan. Allocation of the weights among CPAD and soil and bedrock sensitivities was performed based on observational trends in river pH over the past 30 years. The resulting risk map for surface water acidification showed that large areas of western Japan, as well as smaller areas of Hokkaido, Tohoku, Kanto, and Kyushu, are at high risk of surface water acidification. Seventy-seven percent of all rivers for which a declining trend in pH was observed from 2001 to 2009 were also high-risk areas. Acid deposition might be one factor controlling surface water acidification in areas with high bedrock sensitivity, in addition to high CPAD and soil sensitivity, although the risk of soil acidification remains unclear.

Reconstructing gas distribution maps via an adaptive sparse regularization algorithm

In this paper, we present an algorithm to be used by an inspection robot to produce a gas distribution map and localize gas sources in a large complex environment. The robot, equipped with a remote gas sensor, measures the total absorption of a tuned laser beam and returns integral gas concentrations. A mathematical formulation of such measurement facility is a sequence of Radon transforms, which is a typical ill-posed problem. To tackle the ill-posedness, we develop a new regularization method based on the sparse representation property of gas sources and the adaptive finite-element method. In practice, only a discrete model can be applied, and the quality of the gas distribution map depends on a detailed 3-D world model that allows us to accurately localize the robot and estimate the paths of the laser beam. In this work, using the positivity of measurements and the process of concentration, we estimate the lower and upper bounds of measurements and the exact continuous model (mapping from gas distribution to measurements), and then create a more accurate discrete model of the continuous tomography problem. Based on adaptive sparse regularization, we introduce a new algorithm that gives us not only a solution map but also a mesh map. The solution map more accurately locates gas sources, and the mesh map provides the real gas distribution map. Moreover, the error estimation of the proposed model is discussed. Numerical tests for both the synthetic problem and practical problem are given to show the efficiency and feasibility of the proposed algorithm.

Probabilistic Model to Analyze Patient Accessibility to Medical Facilities Using Geographic Information Systems

In this study, we developed a probabilistic model to analyze patient accessibility to hospitals by using a geographic information system (GIS). In the consideration of patient accessibility, we do not have correct patient addresses because of the laws related to protection of a patient's personal information. Thus, we use a representational place in the city or the ZIP code of the area. However, this may lead to a decline in the accuracy of the analysis. In this study, we used a 500-m mesh map and obtained the population gender and age group data from the national census data, in order to estimate the patient accessibility to medical facilities in small areas. We calculated the probability that a patient lives in each mesh on the basis of the population gender and five-year age group data. We selected the appropriate mesh on the basis of this probability and investigated the time distance from the estimated mesh to each hospital by using a GIS. As a result, we calculated the time distance and its distribution by using the proposed method from limited available information. Further, we found that in the target cities, the average time distance to hospital calculated using the proposed method was longer than that calculated by using a previous method; the percentage of patients who took more time than the city average to reach a hospital by using the proposed method. This method is very useful when planning the geographical resource allocation of medical services.

Shutdown dose rate benchmark experiment at JET to validate the three-dimensional Advanced-D1S method

The paper describes a new benchmark, performed as a preliminary experiment on JET tokamak during the last shutdown. Dose rate has been measured with different dosimeters along the axis of the main horizontal port of Octant 1, from the plasma centre to 1m outside the port at various times after shutdown. The activation dose from the horizontal neutron camera, moved outside the torus hall during the shutdown, has also been assessed. The measured values have been compared with dose rates calculated using an Advanced-D1S method in which new computation capabilities have been introduced, such as dose rate spatial mesh map and automated time behaviour.Measurements along the axis of the horizontal port are well predicted by the calculation. With few exceptions, the D1S estimation is within the error of the measurements. The activation of the horizontal camera is underestimated by a factor of 2. However, more accurate measurements are needed to reduce the uncertainties.The Advanced-D1S method, the results and implications of the benchmark are presented and discussed.

Some Considerations Obtained from Mesh Maps on the Present Situation of Land Use in Osaka Prefecture

Some Considerations Obtained from Mesh Maps on the Present Situation of Land Use in Osaka Prefecture

The Study of Mountain Topography with the Compound Mesh Map in the Boso Hills

The Study of Mountain Topography with the Compound Mesh Map in the Boso Hills

Detection of small leakage from long transportation pipeline with complex noise

In the long distance pipeline remote monitoring system, small leak detection becomes an important issue. Weak singularities in small leak signals are usually difficult to detect precisely under complicated noise background, which may cause false alarm or miss alarm. The advantage of applying the harmonic wavelet method is explored in this paper. Pipeline small leak sensitive characteristics are recognized and the negative pressure wave inflexions are extracted by harmonic wavelet analysis, expressed in terms of harmonic wavelet time-frequency mesh map, time-frequency contour map, and time-frequency profile plot. This paper also presents a comparative study of both Daubechies wavelet and harmonic wavelet analysis when applied to pipeline small leak detection under complicated background noises. Results of simulating test and field experiment show that it is possible to distinguish weak non-stationarities from complicated noises by harmonic wavelet analysis in pipeline small leak detection system. The comparison clearly illustrates that harmonic wavelet based pipeline small leakage detection method is significantly more accurate than other wavelets analysis such as Daubechies wavelet. This work provides a reliable and safe guarantee for oil and gas long distance transportation, reducing petroleum product losses and protecting surrounding environment.

Sensor-Based Scouting Algorithms for Automatic Sampling Tasks in Rough and Large Unstructured Agricultural Fields

Labor shortage has prompted researchers to develop scouting robots to facilitate agriculture field sampling tasks. The purpose of this study was to develop and evaluate sensor-based automatic scouting algorithms for planning efficient paths to guide scouting robots over all sampling points in rough unstructured agricultural environments. A triangular mesh map was used to represent the rough agricultural field surface, with the map incrementally built in simulations. The adapted line-sweeping scouting algorithm was composed of two parts: a coverage algorithm that identified a reasonable coverage path to traverse sampling points, while a dynamic path-planning algorithm determined an optimal path between two adjacent sampling points. Sample points were defined a priori, given a desired spatial sampling density, and the coverage path list was defined as those sample points in sequence of the line-sweeping direction. The coverage task was completed when all accessible sampling points had been traversed. The dynamic path-planning algorithm was used to find the optimal path between adjacent sampling points, circumventing any obstacle between them. The sensor-based scouting algorithm was able to cope with different situations with or without an a priori map or in a partly known environment. The performance of this algorithm has also been evaluated by comparing with two other methods via simulations. Results showed that the path length, energy requirements, and time requirements of the adapted line-sweeping method were less than those for the potential function method and the bug method for four different physical starting points within a single agricultural field. Further, the number of scans required using the adapted line-sweeping method was less than those required for the bug method.

Mapping of First-Frost Days and Risk of Forst Damage to Soybeans

Statistically expected early first-frost days with return periods from 2 to 30 y (EFFDk, where k represents the return period) were calculated by fitting frost records obtained at weather stations to the Weibull distribution function. To create 1 km2 mesh maps of EFFDk, a method to estimate EFFDk was developed by relating k to the normals of daily minimum air temperature (Tm).An equation to calculate the probability of occurrence of the first frost before day x ((P (X ≤ x)) from Tm was derived. Risk of early first-frost damage to soybeans was defined as (P (X ≤ maturity day). Day of maturity was estimated with existing soybean developmental models, and risk maps of first-frost damage to soybeans were created.

Influence of surface geology and mineral deposits on the spatial distributions of elemental concentrations in the stream sediments of Hokkaido, Japan

An elucidation of the background levels of heavy metals, including certain toxic elements, is very essential to accomplish an important environmental assessment. A regional geochemical mapping in Hokkaido, Japan was undertaken by the Geological Survey of Japan, AIST as part of a nationwide geochemical mapping for this purpose. There were 692 stream sediments collected from the active channel (1 sample) / (100 km 2) in Hokkaido and the fine fraction sieved through a 180 μm screen was analyzed using the AAS, ICP-AES, and ICP-MS techniques. The regional geochemical maps for 51 elements were created as a 2000 m mesh map using the geographic information system software. Spatial distribution patterns of elemental concentrations in stream sediments, particularly Neogene–Quaternary volcanic and pyroclastic rocks, are primarily determined by surface geology. The correspondence of elemental concentrations in stream sediments to parent lithology is clearly indicated by ANOVA and a multiple comparison. Sediment samples supplied from mafic volcanic and felsic–mafic pyroclastic rocks are significantly rich in MgO, Al 2O 3, P 2O 5, CaO, Sc, TiO 2, V, MnO, Total (T)-Fe 2O 3, Co, Zn, Sr, and heavy rare earth elements (REEs) (Y and Eu–Lu), but significantly lacking in alkali elements, Be, Nb, light REEs (La–Nd), Ta, Tl, Th, and U. Accretionary complexes with sedimentary rocks derived from sediments are in stark contrast to volcanic and pyroclastic rocks. Accretionary complexes with mafic–ultramafic rock have significantly elevated Nb, Ta, and Th abundances in sediments besides MgO, Cr, Ni, Co, and Cu. This inexplicable result is caused by the mixed distributions of granite and ultramafic–mafic rocks. The watersheds with mineral deposits relate to the high concentrations of certain elements such as Zn, As, and Hg. The geochemically anomalous pattern, which is a map of the regional anomalies, and a scatter diagram were applied to examine the contribution of mineral deposits to MnO, T-Fe 2O 3, Cr, Cu, Zn, As, Cd, Sb, Hg, Pb, and Bi concentrations. Consequently, they were grouped into four types: 1) Mineral deposits with no outliers resulting from mineralization (MnO, T-Fe 2O 3, and Cr), 2) sediments supplied from watersheds without metal deposits conceal high metal inputs from known mineral deposits (Cu), 3) deposits from a geochemically anomalous area that closely relates to the presence of mineral deposits (As, Sb, and Hg), and 4) deposits from the widely altered zone associated with the Kuroko as well as hydrothermal deposits corresponding to geochemically anomalous patterns (Zn, Cd, and Pb). This study provides an important regional geochemical database for a young island-arc setting and interpretational problems, such as complicated geology and active erosion, that are unique to Japan.