scholarly journals A Cross-Site Visual Localization Method for Yutu Rover

2014 ◽  
Vol XL-4 ◽  
pp. 279-284 ◽  
Author(s):  
W. Wan ◽  
Z. Liu ◽  
K. Di ◽  
B. Wang ◽  
J. Zhou
Keyword(s):  
Field Experiments ◽  
Dead Reckoning ◽  
Turnaround Time ◽  
Bundle Adjustment ◽  
Visual Localization ◽  
Planetary Rover ◽  
Localization Method ◽  
Practical Applications ◽  
Accurate Localization ◽  
Cross Site

Localization of the rover is critical to support science and engineering operations in planetary rover missions, such as rover traverse planning and hazard avoidance. It is desirable for planetary rover to have visual localization capability with high degree of automation and quick turnaround time. In this research, we developed a visual localization method for lunar rover, which is capable of deriving accurate localization results from cross-site stereo images. Tie points are searched in correspondent areas predicted by initial localization results and determined by ASIFT matching algorithm. Accurate localization results are derived from bundle adjustment based on an image network constructed by the tie points. In order to investigate the performance of proposed method, theoretical accuracy analysis on is implemented by means of error propagation principles. Field experiments were conducted to verify the effectiveness of the proposed method in practical applications. Experiment results prove that the proposed method provides more accurate localization results (1 %~4 %) than dead-reckoning. After more validations and enhancements, the developed rover localization method has been successfully used in Chang'e-3 mission operations.

scholarly journals A Novel Indoor Localization Method Based on Image Retrieval and Dead Reckoning

2020 ◽  
Vol 10 (11) ◽  
pp. 3803
Author(s):  
Jiuchao Qian ◽  
Yuhao Cheng ◽  
Rendong Ying ◽  
Peilin Liu
Keyword(s):  
Indoor Localization ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Dead Reckoning ◽  
Indoor Navigation ◽  
Two Dimensional ◽  
Localization Method ◽  
Practical Applications ◽  
Cumulative Error ◽  
Starting Point

Indoor pedestrian localization measurement is a hot topic and is widely used in indoor navigation and unmanned devices. PDR (Pedestrian Dead Reckoning) is a low-cost and independent indoor localization method, estimating position of pedestrians independently and continuously. PDR fuses the accelerometer, gyroscope and magnetometer to calculate relative distance from starting point, which is mainly composed of three modules: step detection, stride length estimation and heading calculation. However, PDR is affected by cumulative error and can only work in two-dimensional planes, which makes it limited in practical applications. In this paper, a novel localization method V-PDR is presented, which combines VPR (Visual Place Recognition) and PDR in a loosely coupled way. When there is error between the localization result of PDR and VPR, the algorithm will correct the localization of PDR, which significantly reduces the cumulative error. In addition, VPR recognizes scenes on different floors to correct floor localization due to vertical movement, which extends application scene of PDR from two-dimensional planes to three-dimensional spaces. Extensive experiments were conducted in our laboratory building to verify the performance of the proposed method. The results demonstrate that the proposed method outperforms general PDR method in accuracy and can work in three-dimensional space.

scholarly journals PRECISION OF VISUAL LOCALIZATION USING DYNAMIC GROUND CONTROL POINTS

2020 ◽  
Vol XLIII-B1-2020 ◽  
pp. 363-370
Author(s):  
P. Trusheim ◽  
C. Heipke
Keyword(s):  
Rapid Development ◽  
Sliding Window ◽  
Bundle Adjustment ◽  
Ground Control ◽  
Visual Localization ◽  
Control Points ◽  
Automated Driving ◽  
Sliding Windows ◽  
Ground Control Points

Abstract. Localization is one of the first steps in navigation. Especially due to the rapid development in automated driving, a precise and reliable localization becomes essential. In this paper, we report an investigation of the usage of dynamic ground control points (GCP) in visual localization in an automotive environment. Instead of having fixed positions, dynamic GCPs move together with the camera. As a measure of quality, we employ the precision of the bundle adjustment results. In our experiments, we simulate and investigate different realistic traffic scenarios. After investigating the role of tie points, we compare an approach using dynamic GCPs to an approach with static GCPs to answer the question how a comparable precision can be reached for visual localization. We show, that in our scenario, where two dynamic GCPs move together with a camera, similar results are indeed obtained to using a number of static GCPs distributed over the whole trajectory. In another experiment, we take a closer look at sliding window bundle adjustments. Sliding windows make it possible to work with an arbitrarily large number of images and to still obtain near real-time results. We investigate this approach in combination with dynamic GCPs and vary the no. of images per window.

scholarly journals Gravity-Based Methods for Heading Computation in Pedestrian Dead Reckoning

Sensors ◽  
2019 ◽  
Vol 19 (5) ◽  
pp. 1170 ◽  
Author(s):  
Adi Manos ◽  
Itzik Klein ◽  
Tamir Hazan
Keyword(s):  
Field Experiments ◽  
Dead Reckoning ◽  
Vertical Direction ◽  
Indoor Navigation ◽  
Magnetic Sensors ◽  
Dominant Factor ◽  
Heading Estimation ◽  
Using Data ◽  
Pedestrian Dead Reckoning ◽  
Gravity Direction

One of the common ways for solving indoor navigation is known as Pedestrian Dead Reckoning (PDR), which employs inertial and magnetic sensors typically embedded in a smartphone carried by a user. Estimation of the pedestrian’s heading is a crucial step in PDR algorithms, since it is a dominant factor in the positioning accuracy. In this paper, rather than assuming the device to be fixed in a certain orientation on the pedestrian, we focus on estimating the vertical direction in the sensor frame of an unconstrained smartphone. To that end, we establish a framework for gravity direction estimation and highlight the important role it has for solving the heading in the horizontal plane. Furthermore, we provide detailed derivation of several approaches for calculating the heading angle, based on either the gyroscope or the magnetic sensor, all of which employ the estimated vertical direction. These various methods—both for gravity direction and for heading estimation—are demonstrated, analyzed and compared using data recorded from field experiments with commercial smartphones.

scholarly journals Location-Based Tracking Data and Customer Movement Pattern Analysis Using for Sustainable Fashion Business

2019 ◽  
Vol 11 (22) ◽  
pp. 6209 ◽  
Author(s):  
Jonghyuk Kim ◽  
Hyunwoo Hwangbo ◽  
Sung Jun Kim ◽  
Soyean Kim
Keyword(s):  
Field Experiments ◽  
Pattern Analysis ◽  
Movement Patterns ◽  
Movement Pattern ◽  
Tracking Data ◽  
Discrete Location ◽  
Practical Applications ◽  
Before And After ◽  
Stay Time ◽  
Visual Merchandising

Retailers need accurate movement pattern analysis of human-tracking data to maximize the space performance of their stores and to improve the sustainability of their business. However, researchers struggle to precisely measure customers’ movement patterns and their relationships with sales. In this research, we adopt indoor positioning technology, including wireless sensor devices and fingerprinting techniques, to track customers’ movement patterns in a fashion retail store over four months. Specifically, we conducted three field experiments in three different timeframes. In each experiment, we rearranged one element of the visual merchandising display (VMD) to track and compare customer movement patterns before and after the rearrangement. For the analysis, we connected customers’ discrete location data to identify meaningful patterns in customers’ movements. We also used customers’ location and time information to match identified movement pattern data with sales data. After classifying individuals’ movements by time and sequences, we found that stay time in a particular zone had a greater impact on sales than the total stay time in the store. These results challenge previous findings in the literature that suggest that the longer customers stayed in a store, the more they purchase. Further, the results confirmed that effective store rearrangement could change not only customer movement patterns but also overall sales of store zones. This research can be a foundation for various practical applications of tracking data technologies.

Accurate localization method for subaperture stitching interferometry in aspherical optics metrology

2020 ◽  
Vol 91 (7) ◽  
pp. 075114
Author(s):  
Zhuo Zhao ◽  
Bing Li ◽  
Xiaoqin Kang ◽  
Jiasheng Lu ◽  
Xiang Wei ◽  
...  
Keyword(s):  
Localization Method ◽  
Accurate Localization ◽  
Subaperture Stitching ◽  
Aspherical Optics

scholarly journals AGV Localization System Based on Ultra-Wideband and Vision Guidance

Electronics ◽  
2020 ◽  
Vol 9 (3) ◽  
pp. 448 ◽  
Author(s):  
Xiaohao Hu ◽  
Zai Luo ◽  
Wensong Jiang
Keyword(s):  
Monocular Vision ◽  
Ultra Wideband ◽  
Localization Algorithm ◽  
Localization Accuracy ◽  
Localization Method ◽  
Localization System ◽  
Indoor Location ◽  
Accurate Localization ◽  
Vision Localization ◽  
Automated Storage

Aiming at the problems of low localization accuracy and complicated localization methods of the automatic guided vehicle (AGV) in the current automatic storage and transportation process, a combined localization method based on the ultra-wideband (UWB) and the visual guidance is proposed. Both the UWB localization method and the monocular vision localization method are applied to the indoor location of the AGV. According to the corner points of an ArUco code fixed on the AGV body, the monocular vision localization method can solve the pose information of the AGV by the PnP algorithm in real-time. As an auxiliary localization method, the UWB localization method is called to locate the AGV coordinates. The distance from the tag on the AGV body to the surrounding anchors is measured by the time of flight (TOF) ranging algorithm, and the actual coordinates of the AGV are calculated by the trilateral centroid localization algorithm. Then, the localization data of the UWB is corrected by the mean compensation method to obtain a consistent and accurate localization trajectory. The experiment result shows that this localization system has an error of 15mm, which meets the needs of AGV location in the process of automated storage and transportation.

scholarly journals A Low-Cost Consistent Vehicle Localization Based on Interval Constraint Propagation

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Zhan Wang ◽  
Alain Lambert
Keyword(s):  
Constraint Satisfaction Problem ◽  
Low Cost ◽  
Dead Reckoning ◽  
Constraint Propagation ◽  
Vehicle Localization ◽  
Practical Applications ◽  
Localization And Mapping ◽  
Position And Orientation ◽  
Map Data ◽  
Interval Constraint

Probabilistic techniques (such as Extended Kalman Filter and Particle Filter) have long been used to solve robotic localization and mapping problem. Despite their good performance in practical applications, they could suffer inconsistency problems. This paper proposes an interval analysis based method to estimate the vehicle pose (position and orientation) in a consistent way, by fusing low-cost sensors and map data. We cast the localization problem into an Interval Constraint Satisfaction Problem (ICSP), solved via Interval Constraint Propagation (ICP) techniques. An interval map is built when a vehicle embedding expensive sensors navigates around the environment. Then vehicles with low-cost sensors (dead reckoning and monocular camera) can use this map for ego-localization. Experimental results show the soundness of the proposed method in achieving consistent localization.

An Accurate Localization Method for Video Sensor Network Nodes

2011 ◽  
Vol 225-226 ◽  
pp. 531-535
Author(s):  
Jun Xiang Gao ◽  
Yan Tian
Keyword(s):  
Sensor Networks ◽  
Sensor Node ◽  
Minimum Mean Square Error ◽  
Sensor Nodes ◽  
Network Nodes ◽  
Practical Applications ◽  
Accurate Localization ◽  
Node Location ◽  
Video Sensor Networks ◽  
Video Sensor

Localization of the sensor nodes is a major obstacle for practical applications of video sensor networks. This paper present a novel localization technique based on vision in wireless sensor networks. On the assumption that sensor nodes can be recognized in an image, a sensor node firstly direct its Field-of-View (FoV) to an anchor or localized node, then we can get the orientation of anchor node relate to the sensor node to be localized. If two or more anchors can be found in sensing area, a series of equations will be obtained. They can be solved using minimum mean square error rule, and the solution of the overdetermined equations mentioned above is the estimation of the node position. The experiments indicate that a promising performance can be achieved in determining the exact node location using a small number of anchors.

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