The Design of Simultaneous Location and Mapping System for Intelligent Vehicle in Indoor Environment

2013 ◽  
Vol 302 ◽  
pp. 729-734
Author(s):  
Lei Wang ◽  
Xiao Long Lu ◽  
Zhi Hua Cao
Keyword(s):  
Indoor Environment ◽  
Intelligent Vehicles ◽  
Global Coordinate System ◽  
Coordinate Systems ◽  
Automatic Navigation ◽  
Motion State ◽  
Coordinate Position ◽  
Mapping System ◽  
Simultaneous Location And Mapping ◽  
Coordinate Conversion

A design of simultaneous location and mapping system for intelligent vehicles was proposed. The paper put forward a new algorithm digitalizing motion state which can achieve the automatic navigation and location of the vehicle. Convert the coordinate systems of distance-detecting module with ultrasonic sensors and odometer positioning module to the global coordinate system so as to determine the robot’s global coordinate position and the barrier’s distribution in the environment. The motion environment was represented as a 2-D grid map. The simulation in Visual Studio software can verify that the design is available to establish the simultaneous location and mapping of indoor environment and the algorithm is reliable. The innovation point is that simultaneous location and mapping is achieved by coordinate conversion in the algorithm instead of the complex computing.

Technique for relation global reference system and local realization of global reference system by continuously operated reference stations

2020 ◽  
Vol 962 (8) ◽  
pp. 24-37
Author(s):  
V.E. Tereshchenko
Keyword(s):  
Coordinate System ◽  
Russian Federation ◽  
Reference System ◽  
Main Part ◽  
Precise Point Positioning ◽  
Global Coordinate System ◽  
Coordinate Systems ◽  
Novosibirsk Region ◽  
The Russian Federation

The article suggests a technique for relation global kinematic reference system and local static realization of global reference system by regional continuously operated reference stations (CORS) network. On the example of regional CORS network located in the Novosibirsk Region (CORS NSO) the relation parameters of the global reference system WGS-84 and its local static realization by CORS NSO network at the epoch of fixing stations coordinates in catalog are calculated. With the realization of this technique, the main parameters to be determined are the speed of displacement one system center relativly to another and the speeds of rotation the coordinate axes of one system relatively to another, since the time evolution of most stations in the Russian Federation is not currently provided. The article shows the scale factor for relation determination of coordinate systems is not always necessary to consider. The technique described in the article also allows detecting the errors in determining the coordinates of CORS network in global coordinate system and compensate for them. A systematic error of determining and fixing the CORS NSO coordinates in global coordinate system was detected. It is noted that the main part of the error falls on the altitude component and reaches 12 cm. The proposed technique creates conditions for practical use of the advanced method Precise Point Positioning (PPP) in some regions of the Russian Federation. Also the technique will ensure consistent PPP method results with the results of the most commonly used in the Russian Federation other post-processing methods of high-precision positioning.

Applications of the Global Coordinate System

2011 ◽  
Author(s):  
Yves Balasko
Keyword(s):  
Coordinate System ◽  
Critical Points ◽  
Global Coordinate System ◽  
Coordinate Systems ◽  
Analytical Characterization ◽  
Equilibrium Manifold ◽  
System P ◽  
Definition Of

The global coordinate system for the equilibrium manifold follows from: (1) the determination of the unique fiber F(b) through the equilibrium (ρ‎, ω‎) where b = φ‎((ρ‎, ω‎) = (ρ‎, ρ‎ · ρ‎1, …, ρ‎ · ρ‎m); and (2) the determination of the location of the equilibrium (ρ‎, ω‎) within the fiber F(b) viewed as a linear space of dimension (ℓ − 1)(m − 1) and, therefore, parameterized by (ℓ − 1)(m − 1) coordinates. If there is little leeway in determining the fiber F(b) through the equilibrium (ρ‎, ω‎), there are different ways of representing the equilibrium (ρ‎, ω‎) within its fiber F(b). This leads to the definition of coordinate systems (A) and (B) for the equilibrium manifold. This chapter defines these two coordinate systems and applies them to obtain an analytical characterization of the critical equilibria, i.e., the critical points of the natural projection.

scholarly journals The Accuracy Comparison of Three Simultaneous Localization and Mapping (SLAM)-Based Indoor Mapping Technologies

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3228 ◽  
Author(s):  
Yuwei Chen ◽  
Jian Tang ◽  
Changhui Jiang ◽  
Lingli Zhu ◽  
Matti Lehtomäki ◽  
...  
Keyword(s):  
Indoor Environment ◽  
Simultaneous Localization And Mapping ◽  
Point Clouds ◽  
Medium Size ◽  
Accuracy Evaluation ◽  
Depth Cameras ◽  
Localization And Mapping ◽  
Mapping System ◽  
Small Footprint ◽  
Mapping Systems

The growing interest and the market for indoor Location Based Service (LBS) have been drivers for a huge demand for building data and reconstructing and updating of indoor maps in recent years. The traditional static surveying and mapping methods can’t meet the requirements for accuracy, efficiency and productivity in a complicated indoor environment. Utilizing a Simultaneous Localization and Mapping (SLAM)-based mapping system with ranging and/or camera sensors providing point cloud data for the maps is an auspicious alternative to solve such challenges. There are various kinds of implementations with different sensors, for instance LiDAR, depth cameras, event cameras, etc. Due to the different budgets, the hardware investments and the accuracy requirements of indoor maps are diverse. However, limited studies on evaluation of these mapping systems are available to offer a guideline of appropriate hardware selection. In this paper we try to characterize them and provide some extensive references for SLAM or mapping system selection for different applications. Two different indoor scenes (a L shaped corridor and an open style library) were selected to review and compare three different mapping systems, namely: (1) a commercial Matterport system equipped with depth cameras; (2) SLAMMER: a high accuracy small footprint LiDAR with a fusion of hector-slam and graph-slam approaches; and (3) NAVIS: a low-cost large footprint LiDAR with Improved Maximum Likelihood Estimation (IMLE) algorithm developed by the Finnish Geospatial Research Institute (FGI). Firstly, an L shaped corridor (2nd floor of FGI) with approximately 80 m length was selected as the testing field for Matterport testing. Due to the lack of quantitative evaluation of Matterport indoor mapping performance, we attempted to characterize the pros and cons of the system by carrying out six field tests with different settings. The results showed that the mapping trajectory would influence the final mapping results and therefore, there was optimal Matterport configuration for better indoor mapping results. Secondly, a medium-size indoor environment (the FGI open library) was selected for evaluation of the mapping accuracy of these three indoor mapping technologies: SLAMMER, NAVIS and Matterport. Indoor referenced maps were collected with a small footprint Terrestrial Laser Scanner (TLS) and using spherical registration targets. The 2D indoor maps generated by these three mapping technologies were assessed by comparing them with the reference 2D map for accuracy evaluation; two feature selection methods were also utilized for the evaluation: interactive selection and minimum bounding rectangles (MBRs) selection. The mapping RMS errors of SLAMMER, NAVIS and Matterport were 2.0 cm, 3.9 cm and 4.4 cm, respectively, for the interactively selected features, and the corresponding values using MBR features were 1.7 cm, 3.2 cm and 4.7 cm. The corresponding detection rates for the feature points were 100%, 98.9%, 92.3% for the interactive selected features and 100%, 97.3% and 94.7% for the automated processing. The results indicated that the accuracy of all the evaluated systems could generate indoor map at centimeter-level, but also variation of the density and quality of collected point clouds determined the applicability of a system into a specific LBS.

The Effect of the Accuracy of Various Measuring Devices on Recorded Joint Kinematics

2004 ◽  
Author(s):  
Susan M. Moore ◽  
Mary T. Gabriel ◽  
Maribeth Thomas ◽  
Jennifer Zeminski ◽  
Savio L.-Y. Woo ◽  
...  
Keyword(s):  
Knee Joint ◽  
Coordinate System ◽  
Joint Kinematics ◽  
Optical Tracking ◽  
Global Coordinate System ◽  
Coordinate Systems ◽  
Measurement Device ◽  
Knee Joint Kinematics ◽  
Measurement Devices ◽  
Tracking Device

Knowledge of joint kinematics contributes to the understanding of the function of soft tissue restraints, injury mechanisms, and can be used to evaluate surgical repair techniques. (Tibone, McMahon et al. 1998; Karduna, McClure et al. 2001; Abramowitch, Papageorgiou et al. 2003) Previous studies have measured joint kinematics using a variety of non-invasive methods that include: optical tracking, magnetic tracking, and mechanical linkage systems. (Rudins, Laskowski et al. 1997; Apreleva, Hasselman et al. 1998; Gabriel, Wong et al. 2004) These measurement devices report kinematics of rigid bodies with respect their own global coordinate system. However, it is often useful to understand these kinematics in terms of a coordinate system whose axes coincide with the degrees of freedom of each specific joint (anatomical coordinate systems). Once the kinematics are obtained with respect to the global coordinate system of the measurement device, the joint kinematics can be calculated with respect to anatomical coordinate systems if the relationship between the measurement device and the anatomical coordinate systems are known. Although the accuracy of these kinematic measurement devices is provided by the manufacturer, the effect of their accuracy on joint kinematics reported with respect to anatomical coordinate systems must be determined. (Panjabi, Goel et al. 1982; Crisco, Chen et al. 1994) For example, small errors in orientation of the measurement system could lead to large errors in position for an anatomical coordinate system located at some distance away. As researchers report joint kinematics with respect to the anatomical coordinate systems, understanding the errors produced by one’s measurement device with respect to the anatomical coordinate systems is necessary. Further, a great deal of interest exists for studying knee joint kinematics. (Sakane, Livesay et al. 1999; Lephart, Ferris et al. 2002; Ford, Myer et al. 2003) Within our research center our goal is to collect knee joint kinematics of a cadaver and reproduce them with respect to the anatomical coordinate systems using robotic technology. Therefore, the objective of this study was to determine the effect of the accuracy of three measurement devices (optical tracking device-OptoTrak® 3020, magnetic tracking device-Flock of Birds®, instrumented spatial linkage-EnduraTec Corp.) on knee joint kinematics reported with respect to an anatomical coordinate system.

Interpretation of Ankle Joint Moments during the Stance Phase of Walking: A Comparison of Two Orthogonal Axes Systems

2001 ◽  
Vol 17 (2) ◽  
pp. 173-180 ◽  
Author(s):  
Adrienne E. Hunt ◽  
Richard M. Smith
Keyword(s):  
Coordinate System ◽  
Ankle Joint ◽  
Stance Phase ◽  
Reaction Force ◽  
Frontal Plane ◽  
Transverse Plane ◽  
The Body ◽  
Global Coordinate System ◽  
Coordinate Systems ◽  
Joint Moments

Three-dimensional ankle joint moments were calculated in two separate coordinate systems, from 18 healthy men during the stance phase of walking, and were then compared. The objective was to determine the extent of differences in the calculated moments between these two commonly used systems and their impact on interpretation. Video motion data were obtained using skin surface markers, and ground reaction force data were recorded from a force platform. Moments acting on the foot were calculated about three orthogonal axes, in a global coordinate system (GCS) and also in a segmental coordinate system (SCS). No differences were found for the sagittal moments. However, compared to the SCS, the GCS significantly (p < .001) overestimated the predominant invertor moment at midstance and until after heel rise. It also significantly (p < .05) underestimated the late stance evertor moment. This frontal plane discrepancy was attributed to sensitivity of the GCS to the degree of abduction of the foot. For the transverse plane, the abductor moment peaked earlier (p < .01) and was relatively smaller (p < .01) in the GCS. Variability in the transverse plane was greater for the SCS, and attributed to its sensitivity to the degree of rearfoot inversion. We conclude that the two coordinate systems result in different calculations of nonsagittal moments at the ankle joint during walking. We propose that the body-based SCS provides a more meaningful interpretation of function than the GCS and would be the preferred method in clinical research, for example where there is marked abduction of the foot.

scholarly journals Multitarget Vehicle Tracking and Motion State Estimation Using a Novel Driving Environment Perception System of Intelligent Vehicles

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Yuren Chen ◽  
Xinyi Xie ◽  
Bo Yu ◽  
Yi Li ◽  
Kunhui Lin
Keyword(s):  
State Estimation ◽  
Traffic Safety ◽  
Semantic Segmentation ◽  
Depth Estimation ◽  
Calculation Model ◽  
Intelligent Vehicles ◽  
Vehicle Tracking ◽  
Motion State ◽  
Perception System ◽  
Environment Perception

The multitarget vehicle tracking and motion state estimation are crucial for controlling the host vehicle accurately and preventing collisions. However, current multitarget tracking methods are inconvenient to deal with multivehicle issues due to the dynamically complex driving environment. Driving environment perception systems, as an indispensable component of intelligent vehicles, have the potential to solve this problem from the perspective of image processing. Thus, this study proposes a novel driving environment perception system of intelligent vehicles by using deep learning methods to track multitarget vehicles and estimate their motion states. Firstly, a panoramic segmentation neural network that supports end-to-end training is designed and implemented, which is composed of semantic segmentation and instance segmentation. A depth calculation model of the driving environment is established by adding a depth estimation branch to the feature extraction and fusion module of the panoramic segmentation network. These deep neural networks are trained and tested in the Mapillary Vistas Dataset and the Cityscapes Dataset, and the results showed that these methods performed well with high recognition accuracy. Then, Kalman filtering and Hungarian algorithm are used for the multitarget vehicle tracking and motion state estimation. The effectiveness of this method is tested by a simulation experiment, and results showed that the relative relation (i.e., relative speed and distance) between multiple vehicles can be estimated accurately. The findings of this study can contribute to the development of intelligent vehicles to alert drivers to possible danger, assist drivers’ decision-making, and improve traffic safety.

scholarly journals TOPOLOGICAL 3D MODELING USING INDOOR MOBILE LIDAR DATA

2015 ◽  
Vol XL-4/W5 ◽  
pp. 13-18 ◽  
Author(s):  
M. Nakagawa ◽  
T. Yamamoto ◽  
S. Tanaka ◽  
M. Shiozaki ◽  
T. Ohhashi
Keyword(s):  
3D Modeling ◽  
Point Cloud ◽  
Indoor Environment ◽  
Lidar Data ◽  
Range Image ◽  
Mobile Mapping ◽  
Massive Point ◽  
Surface Estimation ◽  
Mapping System ◽  
Mobile Mapping System

We focus on a region-based point clustering to extract a polygon from a massive point cloud. In the region-based clustering, RANSAC is a suitable approach for estimating surfaces. However, local workspace selection is required to improve a performance in a surface estimation from a massive point cloud. Moreover, the conventional RANSAC is hard to determine whether a point lies inside or outside a surface. In this paper, we propose a method for panoramic rendering-based polygon extraction from indoor mobile LiDAR data. Our aim was to improve region-based point cloud clustering in modeling after point cloud registration. First, we propose a point cloud clustering methodology for polygon extraction on a panoramic range image generated with point-based rendering from a massive point cloud. Next, we describe an experiment that was conducted to verify our methodology with an indoor mobile mapping system in an indoor environment. This experiment was wall-surface extraction using a rendered point cloud from some viewpoints over a wide indoor area. Finally, we confirmed that our proposed methodology could achieve polygon extraction through point cloud clustering from a complex indoor environment.

scholarly journals A 64-Line Lidar-Based Road Obstacle Sensing Algorithm for Intelligent Vehicles

2018 ◽  
Vol 2018 ◽  
pp. 1-7 ◽  
Author(s):  
Hai Wang ◽  
Xinyu Lou ◽  
Yingfeng Cai ◽  
Long Chen
Keyword(s):  
Real Time ◽  
Clustering Algorithm ◽  
Good Accuracy ◽  
Intelligent Vehicles ◽  
Svm Classifier ◽  
Distance Threshold ◽  
The Road ◽  
Time Performance ◽  
Motion State ◽  
Time Requirements

Based on the 64-line lidar sensor, an object detection and classification algorithm with both effectiveness and real time is proposed. Firstly, a multifeature and multilayer lidar points map is used to separate the road, obstacle, and suspension object. Then, obstacle grids are clustered by a grid-clustering algorithm with dynamic distance threshold. After that, by combining the motion state information of two adjacent frames, the clustering results are corrected. Finally, the SVM classifier is used to classify obstacles with clustered object position and attitude features. The good accuracy and real-time performance of the algorithm are proved by experiments, and it can meet the real-time requirements of the intelligent vehicles.

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