Dynamic GNSS Mission Planning Using DTM for Precise Navigation of Autonomous Vehicles

2016 ◽  
Vol 70 (3) ◽  
pp. 483-504 ◽  
Author(s):  
Aleksander Nowak

Nowadays, the most widely used method for estimating location of autonomous vehicles in real time is the use of Global Navigation Satellite Systems (GNSS). However, positioning in urban environments using GNSS is hampered by poor satellite geometry due to signal obstruction created by both man-made and natural features of the urban environment. The presence of obstacles is the reason for the decreased number of observed satellites as well as uncertainty of GNSS positioning. It is possible that in some sections of the vehicle route there might not be enough satellites necessary to fix position. It is common to use software for static GNSS measurement campaign planning, but it is often only able to predict satellite visibility at one point. This article presents a proposal for dynamic GNSS mission planning using a Digital Terrain Model (DTM) and dead reckoning. The methodology and sample results of numerical experiments are also described. They clearly show that proper dynamic GNSS mission planning is necessary in order to complete a task by an autonomous vehicle in an obstructed environment.

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4236
Author(s):  
Woosik Lee ◽  
Hyojoo Cho ◽  
Seungho Hyeong ◽  
Woojin Chung

Autonomous navigation technology is used in various applications, such as agricultural robots and autonomous vehicles. The key technology for autonomous navigation is ego-motion estimation, which uses various sensors. Wheel encoders and global navigation satellite systems (GNSSs) are widely used in localization for autonomous vehicles, and there are a few quantitative strategies for handling the information obtained through their sensors. In many cases, the modeling of uncertainty and sensor fusion depends on the experience of the researchers. In this study, we address the problem of quantitatively modeling uncertainty in the accumulated GNSS and in wheel encoder data accumulated in anonymous urban environments, collected using vehicles. We also address the problem of utilizing that data in ego-motion estimation. There are seven factors that determine the magnitude of the uncertainty of a GNSS sensor. Because it is impossible to measure each of these factors, in this study, the uncertainty of the GNSS sensor is expressed through three variables, and the exact uncertainty is calculated. Using the proposed method, the uncertainty of the sensor is quantitatively modeled and robust localization is performed in a real environment. The approach is validated through experiments in urban environments.


2021 ◽  
Vol 13 (22) ◽  
pp. 4525
Author(s):  
Junjie Zhang ◽  
Kourosh Khoshelham ◽  
Amir Khodabandeh

Accurate and seamless vehicle positioning is fundamental for autonomous driving tasks in urban environments, requiring the provision of high-end measuring devices. Light Detection and Ranging (lidar) sensors, together with Global Navigation Satellite Systems (GNSS) receivers, are therefore commonly found onboard modern vehicles. In this paper, we propose an integration of lidar and GNSS code measurements at the observation level via a mixed measurement model. An Extended Kalman-Filter (EKF) is implemented to capture the dynamic of the vehicle movement, and thus, to incorporate the vehicle velocity parameters into the measurement model. The lidar positioning component is realized using point cloud registration through a deep neural network, which is aided by a high definition (HD) map comprising accurately georeferenced scans of the road environments. Experiments conducted in a densely built-up environment show that, by exploiting the abundant measurements of GNSS and high accuracy of lidar, the proposed vehicle positioning approach can maintain centimeter-to meter-level accuracy for the entirety of the driving duration in urban canyons.


Agronomy ◽  
2019 ◽  
Vol 9 (5) ◽  
pp. 230 ◽  
Author(s):  
Luisa Martelloni ◽  
Marco Fontanelli ◽  
Stefano Pieri ◽  
Christian Frasconi ◽  
Lisa Caturegli ◽  
...  

Before the introduction of positioning technologies in agriculture practices such as global navigation satellite systems (GNSS), data collection and management were time-consuming and labor-intensive tasks. Today, due to the introduction of advanced technologies, precise information on the performance of agricultural machines, and smaller autonomous vehicles such as robot mowers, can be collected in a relatively short time. The aim of this work was to track the performance of a robot mower in various turfgrass areas of an equal number of square meters but with four different shapes by using real-time kinematic (RTK)-GNSS devices, and to easily extract data by a custom built software capable of calculating the distance travelled by the robot mower, the forward speed, the cutting area, and the number of intersections of the trajectories. These data were then analyzed in order to provide useful functioning information for manufacturers, entrepreneurs, and practitioners. The path planning of the robot mower was random and the turfgrass area for each of the four shapes was 135 m2 without obstacles. The distance travelled by the robot mower, the mean forward speed, and the intersections of the trajectories were affected by the interaction between the time of cutting and the shape of the turfgrass. For all the different shapes, the whole turfgrass area was completely cut after two hours of mowing. The cutting efficiency decreased by increasing the time, as a consequence of the increase in overlaps. After 75 minutes of cutting, the efficiency was about 35% in all the turfgrass areas shapes, thus indicating a high level of overlapping.


Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4209 ◽  
Author(s):  
Suraj Bijjahalli ◽  
Roberto Sabatini ◽  
Alessandro Gardi

One of the primary challenges facing Urban Air Mobility (UAM) and the safe integration of Unmanned Aircraft Systems (UAS) in the urban airspace is the availability of robust, reliable navigation and Sense-and-Avoid (SAA) systems. Global Navigation Satellite Systems (GNSS) are typically the primary source of positioning for most air and ground vehicles and for a growing number of UAS applications; however, their performance is frequently inadequate in such challenging environments. This paper performs a comprehensive analysis of GNSS performance for UAS operations with a focus on failure modes in urban environments. Based on the analysis, a guidance strategy is developed which accounts for the influence of urban structures on GNSS performance. A simulation case study representative of UAS operations in urban environments is conducted to assess the validity of the proposed approach. Results show improved accuracy (approximately 25%) and availability when compared against a conventional minimum-distance guidance strategy.


Vehicles ◽  
2021 ◽  
Vol 3 (4) ◽  
pp. 721-735
Author(s):  
Mohammed Alharbi ◽  
Hassan A. Karimi

Sensor uncertainty significantly affects the performance of autonomous vehicles (AVs). Sensor uncertainty is predominantly linked to sensor specifications, and because sensor behaviors change dynamically, the machine learning approach is not suitable for learning them. This paper presents a novel learning approach for predicting sensor performance in challenging environments. The design of our approach incorporates both epistemic uncertainties, which are related to the lack of knowledge, and aleatoric uncertainties, which are related to the stochastic nature of the data acquisition process. The proposed approach combines a state-based model with a predictive model, where the former estimates the uncertainty in the current environment and the latter finds the correlations between the source of the uncertainty and its environmental characteristics. The proposed approach has been evaluated on real data to predict the uncertainties associated with global navigation satellite systems (GNSSs), showing that our approach can predict sensor uncertainty with high confidence.


Author(s):  
Przemysław Falkowski-Gilski

Today, thanks to mobile devices, satellite communication is available to anyone and everywhere. Gaining information on one’s position using GNSS (Global Navigation Satellite Systems), particularly in unknown urban environments, had become an everyday activity. With the widespread of mobile devices, particularly smartphones, each person can obtain information considering his or her location anytime and everywhere. This paper is focused on a study, considering the quality of satellite communication in case of selected mobile terminals. It describes a measurement campaign carried out in varying urban environments, including a set of Android-powered smartphones coming from different manufacturers. Based on this, respective conclusions and remarks are given, which can aid consumers as well as device manufacturers and application developers.


Author(s):  
P. Jende ◽  
F. Nex ◽  
M. Gerke ◽  
G. Vosselman

Mobile Mapping (MM) has gained significant importance in the realm of high-resolution data acquisition techniques. MM is able to record georeferenced street-level data in a continuous (laser scanners) and/or discrete (cameras) fashion. MM’s georeferencing relies on a conjunction of Global Navigation Satellite Systems (GNSS), Inertial Measurement Units (IMU) and optionally on odometry sensors. While this technique does not pose a problem for absolute positioning in open areas, its reliability and accuracy may be diminished in urban areas where high-rise buildings and other tall objects can obstruct the direct line-of-sight between the satellite and the receiver unit. Consequently, multipath measurements or complete signal outages impede the MM platform’s localisation and may affect the accurate georeferencing of collected data. This paper presents a technique to recover correct orientation parameters for MM imaging platforms by utilising aerial images as an external georeferencing source. This is achieved by a fully automatic registration strategy which takes into account the overall differences between aerial and MM data, such as scale, illumination, perspective and content. Based on these correspondences, MM data can be verified and/or corrected by using an adjustment solution. The registration strategy is discussed and results in a success rate of about 95 %.


2020 ◽  
Vol 09 (01) ◽  
pp. 65-72
Author(s):  
Mohanad Alnuaimi ◽  
Mario G. Perhinschi

This paper is focused on analyzing effects of several significant parameters on the performance of an immunity-inspired methodology for autonomous navigation of unmanned air vehicles when measurements from global navigation satellite systems (GNSS) or similar current sources, including external information of opportunity, are not available. An artificial immune system (AIS) provides corrections to a dead reckoning algorithm for adequate estimates of vehicle position and velocity. Parameter effects are assessed and analyzed through simulation in terms of trajectory tracking errors during autonomous flight.


Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4483
Author(s):  
Daniel Egea-Roca ◽  
Antonio Tripiana-Caballero ◽  
José López-Salcedo ◽  
Gonzalo Seco-Granados ◽  
Wim De Wilde ◽  
...  

Global Navigation Satellite Systems (GNSSs) have become a ubiquitous tool for our modern society to carry out vital tasks such as transportation, civil engineering or precision agriculture. This breath has reached the realm of safety-critical applications such as time management of critical infrastructures or autonomous vehicles, in which GNSS is an essential tool nowadays. Unfortunately, current GNSS performance is not enough to fulfill the requirements of these professional and critical applications. For this reason, the FANTASTIC project was launched to boost the adoption of these applications. The project was funded by the European GNSS agency (GSA) in order to enhance the robustness and accuracy of GNSS in harsh environments. This paper presents the part related to the development of a weighting and exclusion function with a dual circularly polarized antenna. The idea is to reduce the effects of multipath by weighting and/or excluding those measurements affected by multipath. The observables and other metrics obtained from a dual polarized antenna will be exploited to define an exclusion threshold and to provide the weights. Real-world experiments will show the improvement in the positioning solution, using all available constellations, obtained with the developed technique.


Robotics ◽  
2020 ◽  
Vol 9 (3) ◽  
pp. 66
Author(s):  
Oguz Kagan Isik ◽  
Juhyeon Hong ◽  
Ivan Petrunin ◽  
Antonios Tsourdos

The increasing use of Unmanned Aerial Vehicles (UAVs) in safety-critical missions in both civilian and military areas demands accurate and reliable navigation, where one of the key sources of navigation information is presented by Global Navigation Satellite Systems (GNSS). In challenging conditions, for example, in urban areas, the accuracy of GNSS-based navigation may degrade significantly due to user-satellite geometry and obscuration issues without being noticed by the user. Therefore, considering the essentially dynamic rate of change in this type of environment, integrity monitoring is of critical importance for understanding the level of trust we have in positioning and timing data. In this paper, the dilution of precision (DOP) coefficients under nominal and challenging conditions were investigated for the purpose of integrity monitoring in urban environments. By analyzing positioning information in a simulated urban environment using a software-based GNSS receiver, the integrity monitoring approach based on joint consideration of GNSS observables and environmental parameters has been proposed. It was shown that DOP coefficients, when considered together with a number of visible satellites and cut-off elevations specific to the urban environment carry valuable integrity information that is difficult to get using existing integrity monitoring approaches. This has allowed generating indirect integrity measures based on cut-off elevation and satellite visibility that can be used for UAV path planning and guidance in urban environments.


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