Emerging Positioning Technologies and GNSS Augmentations
Chair: Laura Ruotsalainen (University of Helsinki, Finland)
Vice-Chair: Ruizhi Chen (Wuhan University, China)
Terms of Reference
The global availability of position, velocity and time information due to the maturation of GNSS technologies is creating an increasing demand for more and more accurate and reliable solutions for navigation in also GNSS challenging areas.
At present, navigation is mainly based on the use of Global Navigation Satellite Systems (GNSS), providing good performance in open outdoor environments. However, navigation solution with sufficient accuracy and integrity is needed in urban canyons and indoors, where GNSS is significantly degraded or unavailable. For overcoming the aforementioned navigation challenges, research has been very active for decades for finding a suitable set of other methods for augmenting or replacing the use of GNSS in positioning. As well, safety critical applications such as navigation of autonomous systems require use of multiple technologies.
The SC 4.1 focuses on research using specific technologies, like computer vision for navigation or use of 3D point clouds for situational awareness, platforms like smartphones with low-cost positioning sensors, fusion of multi-sensor measurements and applications such as autonomous systems and localization at urban canyons.
• Developing methods for multi-sensor navigation
• Studying and solving navigation problems for safety critical applications such as autonomous driving.
• Formation of 3D point clouds for spatio-temporal monitoring
• Development of computer vision technologies for navigation
• Use of smartphone as a positioning platform
• Localization in deep urban canyons
Program of activities
• To promote research collaboration among groups from geodesy and other branches worldwide dealing with emerging positioning research and applications
• To organize and/or participate in scientific and professional meetings (workshops, conference sessions, etc.)
• To maintain a web page concatenating the Sub-Commission activities and reports
• To encourage special issues on research, applications, and activities related to the topics of this Sub-Commission
• Close co-operations with other elements of the IAG structure and other international organizations such as FIG and ISPRS
Overview of Joint Study Groups (JSG) and Working Groups (WG) of the SC 4.1
• WG 4.1.1 Multi-Sensor Systems
• WG 4.1.2 Autonomous Navigation for Unmanned Systems
• WG 4.1.3 3D point cloud based spatio-temporal Monitoring
• WG 4.1.4 Computer Vision in Navigation
• SSG 4.1.1 Positioning using smartphones
• SSG 4.1.2 Localization at Asian urban canyons
WG 4.1.1 Multi-Sensor Systems
Chair: Allison Kealy (Australia)
Vice-Chair: Gunther Retscher (Austria)
This group is a joint working group between IAG and FIG. It focuses on the development of shared resources that extend our understanding of the theory, tools and technologies applicable to the development of multi-sensor systems.
The group has a major focus on:
• performance characterization of positioning sensors and technologies that can play a role in augmenting core GNSS capabilities,
• theoretical and practical evaluation of current algorithms for measurement integration within multi-sensor systems,
• the development of new measurement integration algorithms based around innovative modeling techniques in other research domains such as machine learning and genetic algorithms, spatial cognition etc.,
• establishing links between the outcomes of this WG and other IAG and FIG WGs (across the whole period),
• generating formal parameters that describe the performance of current and emerging positioning technologies that can inform IAG and FIG members.
Specific projects to be undertaken include:
• international field experiments and workshops on a range of multi sensor systems and technologies.
• evaluation of UAV capabilities and the increasing role of multi-sensor systems in UAV navigation.
• investigation of the role of vision based measurements in improving the navigation performance of multi-sensor systems.
• development of shared resources to encourage rapid research and advancements internationally.
WG 4.1.2 Autonomous Navigation for Unmanned Systems
Chair: Ling Pei (China, email@example.com)
Vice-Chair: Giorgio Guglieri (Italy, firstname.lastname@example.org)
Unmanned systems (e.g., UAV, driverless vehicles, and robots) have become increasingly important for data acquisition in numerous geospatial applications. In recent years, technological advancements have facilitated the manufacturing of various types of intelligent sensors, such as cameras, LiDAR, motion, wireless, magnetic, light, and ultrasonic ones. These sensors and their enabling multi-sensor autonomous systems have potential to be promoted into the geospatial world such as autonomous vehicles, robotics, smart cities, geolocation, condition monitoring, and context awareness.
The Working Group will focus on the challenges for autonomous navigation using unmanned systems. Although extensive research efforts have been paid to sensors, algorithms, architectures, and applications of unmanned systems, it is still challenging to establish smart, autonomous, and disruptive implementations. Examples of the challenges include enabling robust navigation data acquisition in challenging environments, using crowdsourcing techniques to generate and use multi-source navigation databases, designing low-cost low-power autonomous navigation systems, and cloud and edge computation of multi-sensor navigation data, etc.
The group has a major focus on:
• Specification, characterization, and evaluation of the autonomous navigation system requirements in various scenarios
• Technological challenges and emerging applications of UAVs
• New sensors, platforms, and sensors for unmanned vehicle navigation
• Regulations and social impacts on unmanned vehicles
• Scalable multi-sensor integration architectures and technologies for unmanned vehicles
• Self-improving and adaptive navigation systems
• Location-based interactive between autonomous vehicles and human
• Artificial intelligent techniques for environment perception, awareness, data processing, and decision making in unmanned vehicles
• Advanced computation techniques in autonomous navigation systems
Specific projects to be undertaken include:
• Specification, characterization, and evaluation of the system requirements
• Optimal set of sensors and technologies for robust unmanned navigation
• Advantages, challenges, analysis, and application of selected systems
• Relation between autonomous navigation and existing navigation applications
• Relation between autonomous vehicles and human
• Adaptation of navigation sensors and algorithms in various environments
WG 4.1.3 3D Point Cloud Based Spatio-Temporal Monitoring
Chair: Jens-Andre Paffenholz (Germany; email@example.com)
Vice-Chair: Corinna Harmening (Austria; firstname.lastname@example.org)
The group has a major focus on:
• Pick up the items from the previous period with focus on data evaluation, algorithm development in the direction of meaningful comparison of 3D point clouds of different epochs/measurement times (similar to classical deformation monitoring)
• Evaluate the object’s abstraction for epochal comparison by means of discrete point-wise, areas-based and shape based approaches. One suitable method to investigate will be B-spline surfaces.
• Investigate and develop suitable algorithms for change tracking over time in 3D point clouds for instance by means of feature point tracking or shape matching.
• Evaluate the fusion of heterogeneous data like 3D point clouds and ground-based synthetic aperture radar (GB-SAR) data with respect to structural health monitoring applications of, e.g., infrastructure buildings.
• Algorithms will be implemented in Python, Matlab, C++ and for basic 3D point cloud operations should be used open source libraries, e.g., point cloud library (PCL)
• Strengthen the international visibility by cooperating with
WG 4.1.4 Computer Vision in Navigation
Chair: Andrea Masiero (Italy, email@example.com)
SG 4.1.1 Positioning Using Smartphones
Coordinators: Gunther Retscher (Austria), Ruizhi Chen (China)
With the increasing ubiquity of smartphones and tablets, users are now routinely carrying a variety of sensors with them wherever they go. These devices are enabling technologies for ubiquitous computing, facilitating continuous updates of a user’s context. They have built-in GNSS (Global Navigation Satellite Systems), Wi-Fi (Wireless Fidelity), Bluetooth, cameras, MEMS-based inertial sensors, etc. Sensor fusion techniques are required to enable robust positioning and navigation in complex environments needed by consumer users, vehicles, and pedestrians. The SG will be dealing with current developments of such technologies and techniques.
Within the next four years we will focus on:
• Specification, characterization, and evaluation of smartphone positioning and navigation system requirements
• Emerging technologies and techniques and their usage
• Absolute and relative positioning technologies and techniques
• Usage of signals-of-opportunity from different systems, such as Wi-Fi, Ultra-wide Band (UWB), Bluetooth iBeacons, etc.
• Inertial MEMS-based sensors positioning and their integration
• Vision-based positioning with smartphone cameras
• Development of robust sensor fusion algorithms
SG 4.1.2 Positioning and Navigation in Asian Urban Canyons
Coordinators: Li-Ta Hsu (Hong Kong), Kubo Nobuaki (Japan)
The group members proposed this idea in ION (Institute of Navigation) Council Meeting on 16 September 2019 at Miami, Florida, US. The council supported the idea and suggested the group members to discuss with Prof Allison Kealy (RMIT) and Prof Charles Toth (Ohio State) on this initiative. Prof Kealy suggested this initiative may become a special study group for (IAG International Association of Geodesy) to make it as joint effort from IAG and ION.
Locations for data collection:
Urban canyons in Tokyo, Japan and Hong Kong, which we believe they are the most challenging positioning areas in the city environments. Examples of the targeted environments are shown below:
• Open-Sourcing Localization Data Collected in Asian Urban Canyons, including Tokyo and Hong Kong
• Benchmarking different positioning algorithms using the open-sourcing data
• Raising the awareness of the urgent navigation requirement in highly-urbanized areas especially in Asian-Pacific regions.