An autonomous mobile robot with a 3D laser range finder for 3D exploration and digitalization of indoor environments

Digital 3D models of the environment are needed in rescue and inspection robotics, facility managements and architecture. This paper presents an automatic system for gaging and digitalization of 3D indoor environments. It consists of an autonomous mobile robot, a reliable 3D laser range finder and three elaborated software modules. The first module, a fast variant of the Iterative Closest Points algorithm, registers the 3D scans in a common coordinate system and relocalizes the robot. The second module, a next best view planner, computes the next nominal pose based on the acquired 3D data while avoiding complicated obstacles. The third module, a closed-loop and globally stable motor controller, navigates the mobile robot to a nominal pose on the base of odometry and avoids collisions with dynamical obstacles. The 3D laser range finder acquires a 3D scan at this pose. The proposed method allows one to digitalize large indoor environments fast and reliably without any intervention and solves the SLAM problem. The results of two 3D digitalization experiments are presented using a fast octree-based visualization method.     

Automatic 3d free form shape matching using the graduated assignment algorithm

Three-dimensional free form shape matching is a fundamental problem in both the machine vision and pattern recognition literatures. However, the automatic approach to 3D free form shape matching still remains open. In this paper, we propose using k closest points in the second view for the automatic 3D free form shape matching. For the sake of computational efficiency, the optimised k-D tree is employed for the search of the k closest points. Since occlusion and appearance and disappearance of points almost always occur, slack variables have to be employed, explicitly modelling outliers in the process of matching. Then the relative quality of each possible point match is estimated using the graduated assignment algorithm, leading the camera motion parameters to be estimated by the quaternion method in the weighted least-squares sense. The experimental results based on both synthetic data and real images without any pre-processing show the effectiveness and efficiency of the proposed algorithm for the automatic matching of overlapping 3D free form shapes with either sparse or dense points.     

Scan matching SLAM in underwater environments

This paper proposes a pose-based algorithm to solve the full simultaneous localization and mapping problem for autonomous underwater vehicle (AUV) navigating in unknown and possibly unstructured environments. The proposed method first estimates the local path traveled by the robot while forming the acoustic image (scan) with range data coming from a mono-beam rotating sonar head, providing position estimates for correcting the distortions that the vehicle motion produces in the scans. Then, consecutive scans are cross-registered under a probabilistic scan matching technique for estimating the displacements of the vehicle including the uncertainty of the scan matching result. Finally, an augmented state extended Kalman filter estimates and keeps the registered scans poses. No prior structural information or initial pose are considered. The viability of the proposed approach has been tested reconstructing the trajectory of a guided AUV operating along a 600 m path within a marina environment.     

城市地下管网三维可视化实现技术研究

通过分析三维管网可视化模型的实现方式,构建三维管网空间数据模型,选用Flt三维数据图形格式,提出了基于工程测绘数据、纸质蓝图和DXF格式CAD文件三种形式的三维管网模型自动构建技术;基于Vega Prime的场景漫游开发,可将地上建筑、地下岩层、管网等其它Flt模型引入到系统中,共同驱动,实现大场景城市地下管网的快速建模与三维可视化漫游。     

Deformation modeling for robust 3D face matching

Face recognition based on 3D surface matching is promising for overcoming some of the limitations of current 2D image-based face recognition systems. The 3D shape is generally invariant to the pose and lighting changes, but not invariant to the non-rigid facial movement, such as expressions. Collecting and storing multiple templates to account for various expressions for each subject in a large database is not practical. We propose a facial surface modeling and matching scheme to match 2.5D facial scans in the presence of both non-rigid deformations and pose changes (multiview) to a 3D face template. A hierarchical geodesic-based resampling approach is applied to extract landmarks for modeling facial surface deformations. We are able to synthesize the deformation learned from a small group of subjects (control group) onto a 3D neutral model (not in the control group), resulting in a deformed template. A user-specific (3D) deformable model is built by combining the templates with synthesized deformations. The matching distance is computed by fitting this generative deformable model to a test scan. A fully automatic and prototypic 3D face matching system has been developed. Experimental results demonstrate that the proposed deformation modeling scheme increases the 3D face matching accuracy.     

High-speed laser localization for mobile robots

This paper describes a novel, laser-based approach for tracking the pose of a high-speed mobile robot. The algorithm is outstanding in terms of accuracy and computation time. The efficiency is achieved by a closed-form solution for the matching of two laser scans, the use of natural scan features and fast linear filters. The implemented algorithm is evaluated with the high-speed robot Kurt3D (4 m/s), and compared to standard scan matching methods in indoor and outdoor environments.     

Reshaping 3D facial scans for facial appearance modeling and 3D facial expression analysis

3D face scans have been widely used for face modeling and analysis. Due to the fact that face scans provide variable point clouds across frames, they may not capture complete facial data or miss point-to-point correspondences across various facial scans, thus causing difficulties to use such data for analysis. This paper presents an efficient approach to representing facial shapes from face scans through the reconstruction of face models based on regional information and a generic model. A new approach for 3D feature detection and a hybrid approach using two vertex mapping algorithms, displacement mapping and point-to-surface mapping, and a regional blending algorithm are proposed to reconstruct the facial surface detail. The resulting models can represent individual facial shapes consistently and adaptively, establishing facial point correspondences across individual models. The accuracy of the generated models is evaluated quantitatively. The applicability of the models is validated through the application of 3D facial expression recognition using the static 3DFE and dynamic 4DFE databases. A comparison with the state of the art has also been reported.     

基于拓扑高程模型的室外三维环境建模与路径规划

针对复杂室外场景, 提出一种基于拓扑高程模型的三维环境建模方法. 采用自适应可变阈值聚类算法, 将映射到二维水平栅格中的激光点云划分为垂直单元和水平单元, 可实现三维场景中悬空环境特征的有效表述. 在此基础上对垂直单元进行高度离散采样, 从而构建与其相对应的拓扑结构, 并结合BOW (Bag of words)模型对室外三维环境中的典型景物进行辨识. 采用面向拓扑结构和高程图单元的分级匹配策略, 实现不同场景间的精确匹配, 构建具有全局一致性的拓扑高程地图. 利用辨识出来的环境特征和高程地图产生双重环境约束, 实现与室外地形相适应的自主路径规划. 实验结果和数据分析证明了本文环境建模与路径规划方法的有效性和实用性.     

基于机载视频量测的3维城市建模

3维城市模型的快速获取及更新是近十年来计算机视觉及数字摄影测量领域研究的热点。从实用、经济的角度出发，提出了集成城市数字地图、LIDAR data以及机载视频序列影像多数据源，基于数字摄影测量理论的半自动获取3维城市模型的解决办法，并在3维导航的数据生产实践中进行了验证，取得较好的生产效率及效果。     

Grid-based scan-to-map matching for accurate 2D map building

This paper presents a grid-based scan-to-map matching technique for accurate 2D map building. At every acquisition of a new scan, the proposed technique matches the new scan to the previous scan similarly to the conventional techniques, but further corrects the error by matching the new scan to the globally defined map. In order to achieve best scan-to-map matching at each acquisition, the map is represented as a grid map with multiple normal distributions (NDs) in each cell, which is one contribution of this paper. Additionally, the new scan is also represented by NDs, developing a novel ND-to-ND matching technique. This ND-to-ND matching technique has significant potential in the enhancement of the global matching as well as the computational efficiency. Experimental results first show that the proposed technique accumulates very small errors after consecutive matchings and identifies that the scans are matched better to the map with the multi-ND representation than one ND representation. The proposed technique is then tested in a number of large indoor environments, including public domain datasets and the applicability to real world problems is demonstrated.     

A mobile robot based system for fully automated thermal 3D mapping

It is hard to imagine living in a building without electricity and a heating or cooling system these days. Factories and data centers are equally dependent on a continuous functioning of these systems. As beneficial as this development is for our daily life, the consequences of a failure are critical. Malfunctioning power supplies or temperature regulation systems can cause the close-down of an entire factory or data center. Heat and air conditioning losses in buildings lead to a large waste of the limited energy resources and pollute the environment unnecessarily. To detect these flaws as quickly as possible and to prevent the negative consequences constant monitoring of power lines and heat sources is necessary. To this end, we propose a fully automatic system that creates 3D thermal models of indoor environments. The proposed system consists of a mobile platform that is equipped with a 3D laser scanner, an RGB camera and a thermal camera. A novel 3D exploration algorithm ensures efficient data collection that covers the entire scene. The data from all sensors collected at different positions is joined into one common reference frame using calibration and scan matching. In the post-processing step a model is built and points of interest are automatically detected. A viewer is presented that aids experts in analyzing the heat flow and localizing and identifying heat leaks. Results are shown that demonstrate the functionality of the system.     

基于概率模型的2维全局地图建立方法

提出一种激光扫描数据匹配的概率模型,用于移动机器人的全局地图建立。大多数的激光扫描匹配算法都需要利用特征（点或线）来建立对应关系,例如ICP算法。利用正态分布转换概率模型来表示激光扫描,不需利用特征对应,而是通过将扫描得到的离散数据点转换成分段连续可微的概率密度函数,并利用牛顿优化算法来进行扫描匹配,从而建立2维全局地图。实验结果表明,该方法可有效地实时完成室内环境下的2D全局地图建立。     

A Novel Representation and Feature Matching Algorithm for Automatic Pairwise Registration of Range Images

Automatic registration of range images is a fundamental problem in 3D modeling of free-from objects. Various feature matching algorithms have been proposed for this purpose. However, these algorithms suffer from various limitations mainly related to their applicability, efficiency, robustness to resolution, and the discriminating capability of the used feature representation. We present a novel feature matching algorithm for automatic pairwise registration of range images which overcomes these limitations. Our algorithm uses a novel tensor representation which represents semi-local 3D surface patches of a range image by third order tensors. Multiple tensors are used to represent each range image. Tensors of two range images are matched to identify correspondences between them. Correspondences are verified and then used for pairwise registration of the range images. Experimental results show that our algorithm is accurate and efficient. Moreover, it is robust to the resolution of the range images, the number of tensors per view, the required amount of overlap, and noise. Comparisons with the spin image representation revealed that our representation has more discriminating capabilities and performs better at a low resolution of the range images. This work has been provisionally patented under Australian patent number 2004902436 and is sponsored by ARC grant number DP0344338.     

CAD中三维交互技术的研究与实现

本文研究了ＶＲ技术在ＣＡＤ几何造型中作为交互手段的应用,特别研究了三维交互技术在ＣＡＤ中的实现。通过提出一种用于三维交互的精确视觉线索方法,实现了对三维空间中不同信实体相互位置关系的精确感知。探讨了ＣＡＤ中在三维交互技术支持下的新的几何造型技术。     

三维建模技术研究进展

三维建模是许多研究与应用领域的关键技术.对三维建模技术中涉及的三维数据获取与建模方法进行了系统的介绍,重点对激光扫描系统、基于图像建模技术进行了说明与对比.阐述了三维建模技术的最新研究进展及应用.最后指出模型检索研究以及数字化手段存在的问题,对三维建模的研究进行了展望.     

Three-dimensional point cloud plane segmentation in both structured and unstructured environments

This paper focuses on three-dimensional (3D) point cloud plane segmentation. Two complementary strategies are proposed for different environments, i.e., a subwindow-based region growing (SBRG) algorithm for structured environments, and a hybrid region growing (HRG) algorithm for unstructured environments. The point cloud is decomposed into subwindows first, using the points’ neighborhood information when they are scanned by the laser range finder (LRF). Then, the subwindows are classified as planar or nonplanar based on their shape. Afterwards, only planar subwindows are employed in the former algorithm, whereas both kinds of subwindows are used in the latter. In the growing phase, planar subwindows are investigated directly (in both algorithms), while each point in nonplanar subwindows is investigated separately (only in HRG). During region growing, plane parameters are computed incrementally when a subwindow or a point is added to the growing region. This incremental methodology makes the plane segmentation fast. The algorithms have been evaluated using real-world datasets from both structured and unstructured environments. Furthermore, they have been benchmarked against a state-of-the-art point-based region growing (PBRG) algorithm with regard to segmentation speed. According to the results, SBRG is 4 and 9 times faster than PBRG when the subwindow size is set to 3×3 and 4×4 respectively; HRG is 4 times faster than PBRG when the subwindow size is set to 4×4. Open-source code for this paper is available at https://github.com/junhaoxiao/TAMS-Planar-Surface-Based-Perception.git.     

基于倾斜摄影测量的矿产地形三维可视化建模研究

对矿产地形进行三维可视化建模,指导地质勘探,提出基于倾斜摄影测量的矿产地形三维可视化建模方法,采用倾斜摄影测量进行矿产地形的三维图形重建,提取矿产地形的三维边缘轮廓特征量,采用稀疏性的模板特征匹配方法进行矿产地形三维可视化的块匹配,构建矿产地形的边界分布轮廓线,采用不规则三角网重建方法进行矿产地形三维可视化图像的视觉重构,结合倾斜摄影测量方法实现对矿产地形的三维离散点数据重构,提高对矿产地形三维可视化建模的精度。仿真结果表明,采用该方法进行矿产地形三维可视化建模的精度较高,视觉重构效果较好。     

3D registration of laser range scenes by coincidence of coarse binary cubes

Scene registration of a pair of three-dimensional (3D) range images is a 6D optimization problem usually required in mobile robotics. This problem is different from object registration, since all scan directions and depths may contain relevant data, and because farther regions are sampled with lower densities. The paper proposes an efficient scene matching method based on the concept of coarse binary cubes. An integer objective function is defined as the number of coincident cubes between both scans. This is a metric of the degree of overlap that does not employ point distances. Its value is obtained without actually using any 3D grid data structure, with a computational complexity of order O(n), where n represents the number of laser points. This objective function is optimized with a globalized version of the downhill Simplex algorithm to avoid local minima. Experimental results are presented from indoor and outdoor environments with different degrees of structuring. The effect of cube size and the number of vertices on registration performance has been analyzed. Besides, experiments show that the proposed method achieves similar accuracy as iterative closest points (ICP) and normal distribution transform (NDT), while it improves both computation time and robustness against initial misalignments.