scholarly journals THE HANDHELD MOBILE LASER SCANNERS AS A TOOL FOR ACCURATE POSITIONING UNDER FOREST CANOPY

2020 ◽  
Vol XLIII-B1-2020 ◽  
pp. 211-218 ◽  
Author(s):  
J. Chudá ◽  
M. Hunčaga ◽  
J. Tuček ◽  
M. Mokroš
Keyword(s):  
Forest Canopy ◽  
Sustainable Forest Management ◽  
Environmental Data ◽  
Global Navigation Satellite Systems ◽  
Forest Environment ◽  
Positional Accuracy ◽  
Satellite Systems ◽  
Localization And Mapping ◽  
Laser Scanners ◽  
Global Navigation Satellite

Abstract. Nowadays it is important to shift positional accuracy of object measurements under the forest canopy closer to the accuracy standards for land surveys due to the requirements in the field of ecosystem protection, sustainable forest management, property relations, and land register. Simultaneously, it is desirable to use the technology of environmental data acquisition which is not time consuming and cost demanding. Global Navigation Satellite Systems (GNSS) are the most used for positioning today. However, the usefulness and also the accuracy of the measurements with this technology depend on various factors (the strength of the GNSS signal, the geometric position of satellites, the multipath effect etc.). Based on the above mentioned facts, the usability of technology independent of GNSS indicates an ideal solution for positioning under the forest canopy. Several studies have studied the usability of Handheld Mobile Laser Scanners (HMLS) in complex environment. The goal of this paper was to verify a new data collection approach (HMLS with Simultaneous Localization and Mapping (SLAM) technology) for the forest environment practice. The main objective of our study was to reach a precision which complies with the accuracy standards for land surveys. The RMSE of derived positions from point cloud, produced by SLAM devices were 25.3 cm and 28.4 cm, for ZEB REVO and ZEB HORIZON, the handheld mobile laser SLAM scanners used in this study. ZEB HORIZON achieved twice as big accuracy of diameter of breast height (DBH) estimation as ZEB REVO.

scholarly journals LOCALIZATION CORRECTIONS FOR MOBILE LASER SCANNER USING LOCAL SUPPORT-BASED OUTLIER FILTERING

2016 ◽  
Vol III-4 ◽  
pp. 81-88 ◽  
Author(s):  
V. V. Lehtola ◽  
J.-P. Virtanen ◽  
P. Rönnholm ◽  
A. Nüchter
Keyword(s):  
Degrees Of Freedom ◽  
Laser Scanner ◽  
Three Dimensions ◽  
Global Navigation Satellite Systems ◽  
Dimensional Solution ◽  
Satellite Systems ◽  
Localization And Mapping ◽  
Local Support ◽  
Novel Concept ◽  
Global Navigation Satellite

Following the pioneering work introduced in [Lehtola et al., ISPRS J. Photogramm. Remote Sens. 99, 2015, pp. 25–29], we extend the state-of-the-art intrinsic localization solution for a single two-dimensional (2D) laser scanner from one into (quasi) three dimensions (3D). By intrinsic localization, we mean that no external sensors are used to localize the scanner, such as inertial measurement devices (IMU) or global navigation satellite systems (GNSS). Specifically, the proposed method builds on a novel concept of local support-based filtering of outliers, which enables the use of six degrees-of-freedom (DoF) simultaneous localization and mapping (SLAM) for the purpose of enacting appropriate trajectory corrections into the previous one-dimensional solution. Moreover, the local support-based filtering concept is platform independent, and is therefore likely to be widely generalizable. The here presented overall method is yet limited into quasi-3D by its inability to recover trajectories with steep curvature, but in the future, it may be further extended into full 3D.

scholarly journals LOCALIZATION CORRECTIONS FOR MOBILE LASER SCANNER USING LOCAL SUPPORT-BASED OUTLIER FILTERING

2016 ◽  
Vol III-4 ◽  
pp. 81-88 ◽  
Author(s):  
V. V. Lehtola ◽  
J.-P. Virtanen ◽  
P. Rönnholm ◽  
A. Nüchter
Keyword(s):  
Degrees Of Freedom ◽  
Laser Scanner ◽  
Three Dimensions ◽  
Global Navigation Satellite Systems ◽  
Dimensional Solution ◽  
Satellite Systems ◽  
Localization And Mapping ◽  
Local Support ◽  
Novel Concept ◽  
Global Navigation Satellite

Following the pioneering work introduced in [Lehtola et al., ISPRS J. Photogramm. Remote Sens. 99, 2015, pp. 25–29], we extend the state-of-the-art intrinsic localization solution for a single two-dimensional (2D) laser scanner from one into (quasi) three dimensions (3D). By intrinsic localization, we mean that no external sensors are used to localize the scanner, such as inertial measurement devices (IMU) or global navigation satellite systems (GNSS). Specifically, the proposed method builds on a novel concept of local support-based filtering of outliers, which enables the use of six degrees-of-freedom (DoF) simultaneous localization and mapping (SLAM) for the purpose of enacting appropriate trajectory corrections into the previous one-dimensional solution. Moreover, the local support-based filtering concept is platform independent, and is therefore likely to be widely generalizable. The here presented overall method is yet limited into quasi-3D by its inability to recover trajectories with steep curvature, but in the future, it may be further extended into full 3D.

scholarly journals Measuring the Uncertainty of Probabilistic Maps Representing Human Motion for Indoor Navigation

2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Susanna Kaiser ◽  
Maria Garcia Puyol ◽  
Patrick Robertson
Keyword(s):  
Human Motion ◽  
Indoor Navigation ◽  
Global Navigation Satellite Systems ◽  
Indoor Environments ◽  
Satellite Systems ◽  
Mapping Algorithm ◽  
Localization And Mapping ◽  
History Of ◽  
Important Field ◽  
Global Navigation Satellite

Indoor navigation and mapping have recently become an important field of interest for researchers because global navigation satellite systems (GNSS) are very often unavailable inside buildings. FootSLAM, a SLAM (Simultaneous Localization and Mapping) algorithm for pedestrians based on step measurements, addresses the indoor mapping and positioning problem and can provide accurate positioning in many structured indoor environments. In this paper, we investigate how to compare FootSLAM maps via two entropy metrics. Since collaborative FootSLAM requires the alignment and combination of several individual FootSLAM maps, we also investigate measures that help to align maps that partially overlap. We distinguish between the map entropy conditioned on the sequence of pedestrian’s poses, which is a measure of the uncertainty of the estimated map, and the entropy rate of the pedestrian’s steps conditioned on the history of poses and conditioned on the estimated map. Because FootSLAM maps are built on a hexagon grid, the entropy and relative entropy metrics are derived for the special case of hexagonal transition maps. The entropy gives us a new insight on the performance of FootSLAM’s map estimation process.

scholarly journals Study the capabilities of RTK Multi GNSS under forest canopy in regions of Indonesia

2019 ◽  
Vol 94 ◽  
pp. 01021 ◽  
Author(s):  
Heri Andreas ◽  
Hasanuddin Zainal Abidin ◽  
Dina Anggreni Sarsito ◽  
Dhota Pradipta
Keyword(s):  
Real Time ◽  
Forest Canopy ◽  
Global Navigation Satellite Systems ◽  
Navigation Satellite ◽  
Satellite Systems ◽  
Position Accuracy ◽  
The Earth ◽  
Real Time Kinematic ◽  
The Future ◽  
Global Navigation Satellite

For more than two decade, the position on the earth can be precisely determined “real-time” in the order of few centimeters by Real Time Kinematic (RTK) GNSS (Global Navigation Satellite Systems) Method. Nevertheless, few limitations are still recognized such as degradation of accuracy against limited satellite visibilities (e.g. heavy satellite obstructions from forest canopy). It usually takes time to resolve the ambiguities or even in many occasion resulted in failure. Fortunately since recent years to the future seems more satellite systems beside GPS and GLONASS are being launched such as BEIDOU, GALILEO, QZSS, etc. It means that more satellite will be existed above the sky. The term GNSS has changed into Multi GNSS. This Multi GNSS is theoretically adding the value to previous GNSS System like GPS; problems of limited satellite visibilities (e.g. under forest canopy) to the position accuracy perhaps will reduce. Within this paper we try to do study the capabilities of RTK Multi GNSS under forest canopy in Indonesia. We observed by RTK in the forest areas which have canopy of 40 to 90 percent. As conclusion we found improvement in positioning result of even area of very limited satellite visibilities.

scholarly journals Comparing Accuracy of Three Remote Sensing Methods to Evaluate Soil Impact Related to Forest Operations

2020 ◽  
Vol 3 (1) ◽  
pp. 59
Author(s):  
Francesco Latterini ◽  
Rachele Venanzi ◽  
Damiano Tocci ◽  
Federico Moschetti ◽  
Rodolfo Picchio
Keyword(s):  
Remote Sensing ◽  
Sustainable Forest Management ◽  
Central Italy ◽  
Google Earth ◽  
Global Navigation Satellite Systems ◽  
Forest Sector ◽  
Forest Operations ◽  
Proximal Sensing ◽  
Satellite Systems ◽  
Global Navigation Satellite

Monitoring soil impacts related to forest operations is crucial to reach the sustainable forest management goal. On the other hand, field survey to assess such kind of impact is usually costly and time consuming. Therefore, the possibility of using remote and proximal sensing technologies to analyze forest soil impacts could be very helpful for forest managers. According to this, the aim of the present work was the evaluation of reliability of three different remote sensing tools for the assessment of soil impacts related to forest operations. The study area consisted in an oak coppice located in the Municipality of Castel Giorgio (Terni District, Central Italy). The different tested technologies were Sentinel-2, Google Earth and an unmanned aerial vehicle equipped with an RGB sensor. After forest utilization, images of the study area were obtained by the above-mentioned systems, and a photo-interpretation process allowed the identification of skid trails patterns produced by the operators during the extraction of timber. The three theoretical skid trails patterns were compared with the real one, obtained by field relief with Global Navigation Satellite Systems (GNSS) technology. The obtained results showed that all these systems still need some improvements for an effective application in the Italian forest sector, concerning soil impacts evaluation after forest operations.

scholarly journals DIFFERENCES BETWEEN 2009 AND 2016 REVISIONS BASED ON COORDINATES IN GDM2000

2021 ◽  
Vol 6 (24) ◽  
pp. 161-173
Author(s):  
Nur Adilla Zulkifli ◽  
Ami Hassan Md Din ◽  
Wan Anom Wan Aris ◽  
Zheng Yong Chien
Keyword(s):  
Terrestrial Reference Frame ◽  
Peninsular Malaysia ◽  
Global Navigation Satellite Systems ◽  
Ellipsoidal Height ◽  
Positional Accuracy ◽  
Tectonic Plate ◽  
Satellite Systems ◽  
Datum Transformation ◽  
Gnss Network ◽  
Global Navigation Satellite

The Geocentric Datum of Malaysia (GDM200) is realised with respect to International Terrestrial Reference Frame (ITRF) 2000 at epoch 2nd January 2000. In comparison with the 2000 frame, ITRF2014 has significant improvement in terms of its definition and realisation. Moreover, several great earthquakes that struck the Indonesian region for the past decades have deformed the tectonic plate, resulting in a shifted GDM2000. These earthquakes, followed by post-seismic activities, has caused GDM2000 to become obsolete. Following that, the Department of Survey and Mapping Malaysia (DSMM) has taken the initiative to revise the coordinate of Malaysia Real-Time Kinematic Global Navigation Satellite Systems (GNSS) Network (MyRTKnet) stations in GDM2000 into a new set of coordinates. Therefore, this paper presents an effort to analyse the differences between coordinates in GDM2000 based on 2009 and 2016 revisions. In order to measure the discrepancy, forty-seven (47) MyRTKnet stations in Peninsular Malaysia were chosen to estimate the differences between the two (2) revisions. The coordinates obtained from MyRTKnet stations were then projected into Rectified Skewed Orthomorphic (RSO) coordinate system to compute the differences in horizontal position and ellipsoidal height. The finding showed that the discrepancy ranges from 0.8 to 11.8 cm, with the smallest values at SETI station and the biggest value at KRAI station. Meanwhile, for the differences in ellipsoidal height, LIPI station has the biggest value of 8.1 cm, followed by the smallest value of 0.4 cm at SETI station. In conclusion, as the differences in revision gave impact on the changes of coordinates of MyRTKnet stations in Peninsular Malaysia, the frequent revision of GDM2000 should also consider the latest frame to give better positional accuracy, and a proper datum transformation (ITRF2014 to ITRF2000) need to be implemented for mapping purposes.

scholarly journals GNSS/LiDAR-Based Navigation of an Aerial Robot in Sparse Forests

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4061 ◽  
Author(s):  
Antonio C. B. Chiella ◽  
Henrique N. Machado ◽  
Bruno O. S. Teixeira ◽  
Guilherme A. S. Pereira
Keyword(s):  
Autonomous Navigation ◽  
Unscented Kalman Filter ◽  
Unmanned Vehicles ◽  
Global Navigation Satellite Systems ◽  
Fusion Algorithm ◽  
Forest Environment ◽  
Satellite Systems ◽  
Aerial Robot ◽  
Robust Adaptive ◽  
Global Navigation Satellite

Autonomous navigation of unmanned vehicles in forests is a challenging task. In such environments, due to the canopies of the trees, information from Global Navigation Satellite Systems (GNSS) can be degraded or even unavailable. Also, because of the large number of obstacles, a previous detailed map of the environment is not practical. In this paper, we solve the complete navigation problem of an aerial robot in a sparse forest, where there is enough space for the flight and the GNSS signals can be sporadically detected. For localization, we propose a state estimator that merges information from GNSS, Attitude and Heading Reference Systems (AHRS), and odometry based on Light Detection and Ranging (LiDAR) sensors. In our LiDAR-based odometry solution, the trunks of the trees are used in a feature-based scan matching algorithm to estimate the relative movement of the vehicle. Our method employs a robust adaptive fusion algorithm based on the unscented Kalman filter. For motion control, we adopt a strategy that integrates a vector field, used to impose the main direction of the movement for the robot, with an optimal probabilistic planner, which is responsible for obstacle avoidance. Experiments with a quadrotor equipped with a planar LiDAR in an actual forest environment is used to illustrate the effectiveness of our approach.

scholarly journals GEOSPATIAL DATA QUALITY OF THE SERVIR CORS NETWORK

2015 ◽  
Vol II-3/W5 ◽  
pp. 285-290 ◽  
Author(s):  
J. Santos ◽  
R. Teodoro ◽  
N. Mira ◽  
V. B. Mendes
Keyword(s):  
Quality Control ◽  
Geospatial Data ◽  
Global Navigation Satellite Systems ◽  
Positional Accuracy ◽  
Worst Case ◽  
Static Mode ◽  
Satellite Systems ◽  
Gnss Positioning ◽  
Global Navigation Satellite

The SERVIR Continuous Operation Reference Stations (CORS) network was implemented in 2006 to facilitate land surveying with Global Navigation Satellite Systems (GNSS) positioning techniques. Nowadays, the network covers all Portuguese mainland. The SERVIR data is provided to many users, such as surveyors, universities (for education and research purposes) and companies that deal with geographic information. By middle 2012, there was a significant change in the network accessing paradigm, the most important of all being the increase in the responsibility of managing the network to guarantee a permanent availability and the highest quality of the geospatial data. In addition, the software that is used to manage the network and to compute the differential corrections was replaced by a new software package. These facts were decisive to perform the quality control of the SERVIR network and evaluate positional accuracy. In order to perform such quality control, a significant number of geodetic monuments spread throughout the country were chosen. Some of these monuments are located in the worst location regarding the network geometry in order to evaluate the accuracy of positions for the worst case scenarios. Data collection was carried out using different GNSS positioning modes and were compared against the benchmark positions that were determined using data acquired in static mode in 3-hour sessions. We conclude the geospatial data calculated and provided to the users community by the network is, within the surveying purposes, accurate, precise and fits the needs of those users.

scholarly journals Comparison of Different Hardware Configurations for 2D SLAM Techniques Based on Google Cartographer Use Case

2021 ◽  
Author(s):  
Łukasz Sobczak ◽  
Katarzyna Filus ◽  
Joanna Domańska ◽  
Adam Domański
Keyword(s):  
Real Life ◽  
Ground Truth ◽  
Cost Effective ◽  
Global Navigation Satellite Systems ◽  
Use Case ◽  
Indoor Environments ◽  
Satellite Systems ◽  
Localization And Mapping ◽  
Hardware Configuration ◽  
Global Navigation Satellite

Abstract One of the most challenging topics in Robotics is Simultaneous Localization and Mapping (SLAM) in the indoor environments. Due to the fact that Global Navigation Satellite Systems cannot be successfully used in such environments, different data sources are used for this purpose, among others LiDARs (Light Detection and Ranging), which have advanced from numerous other technologies. Other embedded sensors can be used along with LiDARs to improve SLAM accuracy, e.g. the ones available in the Inertial Measurement Units and wheel odometry sensors. Evaluation of different SLAM algorithms and possible hardware configurations in real environments is time consuming and expensive. For that reason, in this paper we evaluate the performance of different hardware configuration used with Google Cartographer SLAM algorithms in simulation framework proposed in 1. Our use case is an actual robot used for room decontamination. The results show that for our robot the best hardware configuration consists of three LiDARs 2D, IMU and wheel odometry sensors. The proposed simulation-based methodology is a cost-effective alternative to real-world evaluation. It allows easy automation and provides access to precise ground truth. It is especially beneficial in the early stages of product design and to reduce the number of necessary real-life tests and hardware configurations.

scholarly journals Rapid Static Positioning Using a Four System GNSS Receivers in the Forest Environment

Forests ◽  
2022 ◽  
Vol 13 (1) ◽  
pp. 45
Author(s):  
Michał Brach
Keyword(s):  
Main Idea ◽  
Global Navigation Satellite Systems ◽  
Forest Environment ◽  
Large Variability ◽  
Satellite Systems ◽  
Forest Inventories ◽  
Cycle Slips ◽  
Gnss Receivers ◽  
Global Navigation Satellite ◽  
Rapid Static Positioning

Global Navigation Satellite Systems (GNSS) are crucial elements used in forest inventories. Forest metrics modeling efficacy depends on the accuracy of determining sample plot locations by GNSS. As of 2021, the GNSS consists of 120 active satellites, ostensibly improving position acquisition in forest conditions. The main idea of this article was to evaluate GIS-class and geodetic class GNSS receivers on 33 control points located in the forest. The main assumptions were operating on four GNSS systems (GPS, GLONASS, Galileo, and BeiDou), keeping a continuous online connection to the network of reference stations, maintaining occupation time-limited to 60 epochs, and repeating all the measurements three times. Rapid static positioning was tested, as it compares the true performance of the four GNSS systems receivers. Statistical differences between the receivers were confirmed. The GIS-class receiver achieved an accuracy of 1.38 m and a precision of 1.29 m, while the geodetic class receiver reached 0.74 m and 0.91 m respectively. Even though the research was conducted under the same data capture conditions, the large variability of positioning results were found to be caused by cycle slips and the multipath effect.

Sign in / Sign up

Export Citation Format

Share Document