A Practical Indoor and Outdoor Seamless Navigation System Based on Electronic Map and Geomagnetism

2021 ◽  
Author(s):  
Kaiyue Qiu ◽  
Ruizhi Chen ◽  
He Huang
Keyword(s):  
Navigation System ◽  
Electronic Map ◽  
Indoor And Outdoor

scholarly journals A Seamless Navigation System and Applications for Autonomous Vehicles Using a Tightly Coupled GNSS/UWB/INS/Map Integration Scheme

2021 ◽  
Vol 14 (1) ◽  
pp. 27
Author(s):  
Changqiang Wang ◽  
Aigong Xu ◽  
Xin Sui ◽  
Yushi Hao ◽  
Zhengxu Shi ◽  
...  
Keyword(s):  
High Precision ◽  
Navigation System ◽  
Autonomous Vehicles ◽  
Outdoor Environment ◽  
Precision Positioning ◽  
Outdoor Environments ◽  
Tightly Coupled ◽  
Seamless Positioning ◽  
Indoor And Outdoor Environments ◽  
Indoor And Outdoor

Seamless positioning systems for complex environments have been a popular focus of research on positioning safety for autonomous vehicles (AVs). In particular, the seamless high-precision positioning of AVs indoors and outdoors still poses considerable challenges and requires continuous, reliable, and high-precision positioning information to guarantee the safety of driving. To obtain effective positioning information, multiconstellation global navigation satellite system (multi-GNSS) real-time kinematics (RTK) and an inertial navigation system (INS) have been widely integrated into AVs. However, integrated multi-GNSS and INS applications cannot provide effective and seamless positioning results for AVs in indoor and outdoor environments due to limited satellite availability, multipath effects, frequent signal blockages, and the lack of GNSS signals indoors. In this contribution, multi-GNSS-tightly coupled (TC) RTK/INS technology is developed to solve the positioning problem for a challenging urban outdoor environment. In addition, ultrawideband (UWB)/INS technology is developed to provide accurate and continuous positioning results in indoor environments, and INS and map information are used to identify and eliminate UWB non-line-of-sight (NLOS) errors. Finally, an improved adaptive robust extended Kalman filter (AREKF) algorithm based on a TC integrated single-frequency multi-GNSS-TC RTK/UWB/INS/map system is studied to provide continuous, reliable, high-precision positioning information to AVs in indoor and outdoor environments. Experimental results show that the proposed scheme is capable of seamlessly guaranteeing the positioning accuracy of AVs in complex indoor and outdoor environments involving many measurement outliers and environmental interference effects.

scholarly journals Hidden Markov Model-based Pedestrian Navigation System using MEMS Inertial Sensors

2015 ◽  
Vol 15 (1) ◽  
pp. 35-43 ◽  
Author(s):  
Yingjun Zhang ◽  
Wen Liu ◽  
Xuefeng Yang ◽  
Shengwei Xing
Keyword(s):  
Markov Model ◽  
Hidden Markov Model ◽  
Navigation System ◽  
Inertial Sensors ◽  
Hidden Markov ◽  
Field Tests ◽  
Model Parameters ◽  
Pedestrian Navigation ◽  
Extraction Algorithm ◽  
Indoor And Outdoor

Abstract In this paper, a foot-mounted pedestrian navigation system using MEMS inertial sensors is implemented, where the zero-velocity detection is abstracted into a hidden Markov model with 4 states and 15 observations. Moreover, an observations extraction algorithm has been developed to extract observations from sensor outputs; sample sets are used to train and optimize the model parameters by the Baum-Welch algorithm. Finally, a navigation system is developed, and the performance of the pedestrian navigation system is evaluated using indoor and outdoor field tests, and the results show that position error is less than 3% of total distance travelled.

Robust Road-Following Navigation System with a Simple Map

2018 ◽  
Vol 30 (4) ◽  
pp. 552-562 ◽  
Author(s):  
Yuki Hosoda ◽  
◽  
Ryota Sawahashi ◽  
Noriaki Machinaka ◽  
Ryota Yamazaki ◽  
...  
Keyword(s):  
Path Planning ◽  
Navigation System ◽  
Autonomous Navigation ◽  
Prior Information ◽  
Electronic Map ◽  
Edge Node ◽  
Road Following ◽  
Environmental Map ◽  
Autonomous Navigation System

This paper presents a novel autonomous navigation system. Our proposed system is based on a simple map (an Edge-Node Graph, which is created from an electronic map). This system consists of “Localization,” which estimates which edge is on the Edge-Node Graph, “Environmental Recognition,” which recognizes the environment around the robot, and “Path Planning,” which avoids objects. Since the robot travels using the Edge-Node Graph, there is no need to prepare an environmental map in advance. In addition, the system is quite robust, since it relies less on prior information. To show the effectiveness of our system, we conducted experiments on each elemental technology as well as some traveling tests.

scholarly journals Indoor and Outdoor Low-Cost Seamless Integrated Navigation System Based on the Integration of INS/GNSS/LIDAR System

2020 ◽  
Vol 12 (19) ◽  
pp. 3271
Author(s):  
Ningbo Li ◽  
Lianwu Guan ◽  
Yanbin Gao ◽  
Shitong Du ◽  
Menghao Wu ◽  
...  
Keyword(s):  
Navigation System ◽  
Low Cost ◽  
Dead Reckoning ◽  
Satellite System ◽  
Outdoor Environment ◽  
Mode Switching ◽  
Integrated Navigation ◽  
Switching Algorithm ◽  
Navigation Algorithm ◽  
Indoor And Outdoor

Global Navigation Satellite System (GNSS) provides accurate positioning data for vehicular navigation in open outdoor environment. In an indoor environment, Light Detection and Ranging (LIDAR) Simultaneous Localization and Mapping (SLAM) establishes a two-dimensional map and provides positioning data. However, LIDAR can only provide relative positioning data and it cannot directly provide the latitude and longitude of the current position. As a consequence, GNSS/Inertial Navigation System (INS) integrated navigation could be employed in outdoors, while the indoors part makes use of INS/LIDAR integrated navigation and the corresponding switching navigation will make the indoor and outdoor positioning consistent. In addition, when the vehicle enters the garage, the GNSS signal will be blurred for a while and then disappeared. Ambiguous GNSS satellite signals will lead to the continuous distortion or overall drift of the positioning trajectory in the indoor condition. Therefore, an INS/LIDAR seamless integrated navigation algorithm and a switching algorithm based on vehicle navigation system are designed. According to the experimental data, the positioning accuracy of the INS/LIDAR navigation algorithm in the simulated environmental experiment is 50% higher than that of the Dead Reckoning (DR) algorithm. Besides, the switching algorithm developed based on the INS/LIDAR integrated navigation algorithm can achieve 80% success rate in navigation mode switching.

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