2020 IEEE/ION Position, Location and Navigation Symposium (PLANS)最新文献_第4页

Stand-Alone Orientation System Based on Visual SLAM 基于Visual SLAM的独立定位系统

2020 IEEE/ION Position, Location and Navigation Symposium (PLANS) Pub Date : 2020-04-01 DOI: 10.1109/PLANS46316.2020.9109974

S. Zotov

引用次数: 0

Development Challenges and Performance Analysis of Drone Visual/Inertial SLAM in a Global Reference System 全球参照系下无人机视觉/惯性SLAM的发展挑战与性能分析

2020 IEEE/ION Position, Location and Navigation Symposium (PLANS) Pub Date : 2020-04-01 DOI: 10.1109/PLANS46316.2020.9110128

Rami Ronen, Anton Jigalin, Z. Berman

{"title":"Development Challenges and Performance Analysis of Drone Visual/Inertial SLAM in a Global Reference System","authors":"Rami Ronen, Anton Jigalin, Z. Berman","doi":"10.1109/PLANS46316.2020.9110128","DOIUrl":"https://doi.org/10.1109/PLANS46316.2020.9110128","url":null,"abstract":"this paper presents a navigation system design for airborne drone-based applications. The proposed operation principle includes visual/inertial tightly coupled integration based on an extended SLAM approach. In addition to the opportunity-based features that are used by similar to the standard SLAM solutions, the proposed approach also utilizes internal landmarks that are created by the algorithm itself. This method allows reducing the drift that is typical in SLAM -based solutions in addition to reducing the algorithm complexity. Adding a small number of global landmarks helps eliminate the remaining drift. The design goal is to use global coordinates during the entire operational cycle. For a 200m altitude flight, with 2 global landmarks, partially available, the system converges fast to high accuracy with respect to the global reference, without any SLAM drift. While for lower altitudes (100 m), only near-tactical grade IMU provides a very low SLAM drift solution. The significance of the work lies in showing the complete design of a global-coordinate drone SLAM system with the fusion of inertial sensors, taking into account tradeoffs on trajectory profile, sensor grades and global landmarks availability.","PeriodicalId":273568,"journal":{"name":"2020 IEEE/ION Position, Location and Navigation Symposium (PLANS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116907002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Novel Approach to Improve Performance of Inertial Navigation System Via Neural Network 利用神经网络提高惯性导航系统性能的新方法

2020 IEEE/ION Position, Location and Navigation Symposium (PLANS) Pub Date : 2020-04-01 DOI: 10.1109/PLANS46316.2020.9110180

Evgeniy Pukhov, H. Cohen

引用次数: 4

Deep Learned Multi-Modal Traffic Agent Predictions for Truck Platooning Cut-Ins 卡车队列切入的深度学习多模式交通代理预测

2020 IEEE/ION Position, Location and Navigation Symposium (PLANS) Pub Date : 2020-04-01 DOI: 10.1109/PLANS46316.2020.9109809

Samuel Paul Douglass, Scott M. Martin, A. Jennings, Howard Chen, D. Bevly

{"title":"Deep Learned Multi-Modal Traffic Agent Predictions for Truck Platooning Cut-Ins","authors":"Samuel Paul Douglass, Scott M. Martin, A. Jennings, Howard Chen, D. Bevly","doi":"10.1109/PLANS46316.2020.9109809","DOIUrl":"https://doi.org/10.1109/PLANS46316.2020.9109809","url":null,"abstract":"Recent advances in Driver-Assisted Truck Platooning (DATP) have shown success in linking multiple trucks in leader-follower platoons using Cooperative Adaptive Cruise Control (CACC). Such set ups allow for closer spacing between trucks which leads to fuel savings. Given that frontal collisions are the most common type of highway accident for heavy trucks, one key issue to truck platooning is handling situations in which vehicles cut-in between platooning trucks. Having more accurate and quicker predictions would improve the safety and efficiency of truck platooning by allowing the control system to react to the intruder sooner and allow for proper spacing before the cutin occurs. Moreover, reduction in false-positives could prevent the CACC from reacting to cut-in vehicles too early, leading to increased benefit from DATP. In this paper, we implement a deep neural network that generates multimodal predictions of traffic agents around a truck platoon. The method uses Long Short-Term Memory networks in an ensemble architecture to predict possible future positions with attached probabilities of vehicles passing by a truck platoon for 5 second horizons. The network performance is compared to a baseline of common state-based predictors including the Constant Velocity Predictor, the Constant Acceleration Predictor, and the Constant Steer Predictor.","PeriodicalId":273568,"journal":{"name":"2020 IEEE/ION Position, Location and Navigation Symposium (PLANS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126120962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Relational Database for PNT Data 关系数据库的PNT数据

2020 IEEE/ION Position, Location and Navigation Symposium (PLANS) Pub Date : 2020-04-01 DOI: 10.1109/PLANS46316.2020.9110134

Sean A. Mochocki, Kyle Kauffman, R. Leishman, J. Raquet

{"title":"Relational Database for PNT Data","authors":"Sean A. Mochocki, Kyle Kauffman, R. Leishman, J. Raquet","doi":"10.1109/PLANS46316.2020.9110134","DOIUrl":"https://doi.org/10.1109/PLANS46316.2020.9110134","url":null,"abstract":"Navigation filter researchers often deal with multiple sets of data collected from different sources. Over time it can be difficult to identify how data was collected and how to model it without sufficient data storage techniques and documentation. A navigation database would allow storage of sets of Position, Navigation and Timing data, along with designated metadata, which would enable future researchers to access and understand historical navigation data. This paper proposes three approaches for a PostgreSQL relational database designed to store navigation test data based on the Scorpion Data Model. Each approach uses different schema for storing navigation data, and identical schema for storing sensor and non-sensor metadata. Using queries designed to be of interest to filter researchers, the authors designed test scripts to rank all three designs according to how quickly the original files could be recreated, and how quickly queries based on sensor, non-sensor, and SDM data returned correct information. In order to test how the different approaches scaled when the databases became larger, these test scripts were used with six databases (two for each approach) with 100 and 1000 logs of repeated navigation test data and randomized metadata. This paper presents the results of these tests, along with a background of relational and NoSQL databases, schema details for each approach, query and testing details, and an analysis of how each approach performed across all tests. Finally, we identify the navigational database schema with the best overall performance based on the data and analysis.","PeriodicalId":273568,"journal":{"name":"2020 IEEE/ION Position, Location and Navigation Symposium (PLANS)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127158520","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

3D Dual-Shell Micro-Resonators for Harsh Environments 用于恶劣环境的3D双壳微谐振器

2020 IEEE/ION Position, Location and Navigation Symposium (PLANS) Pub Date : 2020-04-01 DOI: 10.1109/PLANS46316.2020.9109972

M. Asadian, Danmeng Wang, Yusheng Wang, A. Shkel

引用次数: 7

Matching Maps of Physical and Virtual Radio Transmitters Using Visibility Regions 使用可见区域的物理和虚拟无线电发射机匹配图

2020 IEEE/ION Position, Location and Navigation Symposium (PLANS) Pub Date : 2020-04-01 DOI: 10.1109/PLANS46316.2020.9110139

M. Ulmschneider, C. Gentner, A. Dammann

引用次数: 2

Adaptive Loop-Bandwidth Control Algorithm for Scalar Tracking Loops 标量跟踪环的自适应环带宽控制算法

2020 IEEE/ION Position, Location and Navigation Symposium (PLANS) Pub Date : 2020-04-01 DOI: 10.1109/PLANS46316.2020.9110182

Iñigo Cortés, J. R. V. D. Merwe, A. Rügamer, W. Felber

引用次数: 8

Implementation and performance evaluation of cellular NB-IoT OTDOA positioning 蜂窝NB-IoT OTDOA定位实现及性能评估

2020 IEEE/ION Position, Location and Navigation Symposium (PLANS) Pub Date : 2020-04-01 DOI: 10.1109/PLANS46316.2020.9109877

Mauro Salomon, Stefan Lippuner, Matthias Korb, Qiuting Huang

引用次数: 5

Sub-Degree-Per-Hour MEMS Gyroscope for Measurement While Drilling at 300°C 在300°C钻孔时测量的每小时次度MEMS陀螺仪

2020 IEEE/ION Position, Location and Navigation Symposium (PLANS) Pub Date : 2020-04-01 DOI: 10.1109/PLANS46316.2020.9110136

D. Lin, Robert MacDonald, Dorin Calbaza, B. Scherer, Tammy Johnson, Tim Toepfer, D. Shaddock, E. Andarawis

引用次数: 5