Challenges in Partially-Automated Roadway Feature Mapping Using Mobile Laser Scanning and Vehicle Trajectory Data

Connected vehicle and driver's assistance applications are greatly facilitated by Enhanced Digital Maps (EDMs) that represent roadway features (e.g., lane edges or centerlines, stop bars). Due to the large number of signalized intersections and miles of roadway, manual development of EDMs on a global basis is not feasible. Mobile Terrestrial Laser Scanning (MTLS) is the preferred data acquisition method to provide data for automated EDM development. Such systems provide an MTLS trajectory and a point cloud for the roadway environment. The challenge is to automatically convert these data into an EDM. This article presents a new processing and feature extraction method, experimental demonstration providing SAE-J2735 map messages for eleven example intersections, and a discussion of the results that points out remaining challenges and suggests directions for future research.Comment: 6 pages, 5 figure

ECEF Position Accuracy and Reliability: Inertial Navigation with GNSS Precise Point Positioning (PPP)

This report presents experimental results for a moving platform using GPS PPP data for state estimation. Results from two PPP GPS state estimation approaches are presented: point-wise least squares (LS) and aided inertial navigation (INS). The point-wise LS results provide information about the accuracy and reliability of PPP GPS information at each measurement epoch, independent of other epochs. The INS results show the performance that can be achieved by combining information across measurement epochs. INS results are included for two different grades of IMU: navigation grade and consumer grade.The report cites publications that contain more detailed expla- nations of the GNSS error sources, computation of PPP wide area correction, and the LS and aided INS estimation algorithms

Advanced multilateration theory, software development, and data processing: The MICRODOT system

The process of geometric parameter estimation to accuracies of one centimeter, i.e., multilateration, is defined and applications are listed. A brief functional explanation of the theory is presented. Next, various multilateration systems are described in order of increasing system complexity. Expected systems accuracy is discussed from a general point of view and a summary of the errors is listed. An outline of the design of a software processing system for multilateration, called MICRODOT, is presented next. The links of this software, which can be used for multilateration data simulations or operational data reduction, are examined on an individual basis. Functional flow diagrams are presented to aid in understanding the software capability. MICRODOT capability is described with respect to vehicle configurations, interstation coordinate reduction, geophysical parameter estimation, and orbit determination. Numerical results obtained from MICRODOT via data simulations are displayed both for hypothetical and real world vehicle/station configurations such as used in the GEOS-3 Project. These simulations show the inherent power of the multilateration procedure

Automated Ground Truth Estimation For Automotive Radar Tracking Applications With Portable GNSS And IMU Devices

Baseline generation for tracking applications is a difficult task when working with real world radar data. Data sparsity usually only allows an indirect way of estimating the original tracks as most objects' centers are not represented in the data. This article proposes an automated way of acquiring reference trajectories by using a highly accurate hand-held global navigation satellite system (GNSS). An embedded inertial measurement unit (IMU) is used for estimating orientation and motion behavior. This article contains two major contributions. A method for associating radar data to vulnerable road user (VRU) tracks is described. It is evaluated how accurate the system performs under different GNSS reception conditions and how carrying a reference system alters radar measurements. Second, the system is used to track pedestrians and cyclists over many measurement cycles in order to generate object centered occupancy grid maps. The reference system allows to much more precisely generate real world radar data distributions of VRUs than compared to conventional methods. Hereby, an important step towards radar-based VRU tracking is accomplished.Comment: 10 pages, 9 figures, accepted paper for 2019 20th International Radar Symposium (IRS), Ulm, Germany, June 2019. arXiv admin note: text overlap with arXiv:1905.1121

Модифікований алгоритм зглажування/фільтрації дифференціальних ГНСС спостережень в режимі кінематичного позиціонування

The results of GNSS differential measurements code-phase smoothing/filtering modified algorithmdevelopment and validation have been presented for the mobile objects kinematic positioning. It is shown that theupdated algorithm allows considerable increasing of the positioning accuracy and obtaining a glide coordinatesolution in comparison with the analogs.В статье представлены результаты разработки и верификации модифицированного алгоритма кодово-фазовогосглаживания/фильтрации дифференциальных ГНСС наблюдений в задачах кинематического позиционирования движущихся объектов. Предложенный подход базируется на применении сглаживания/фильтрации в реальномвремени кодовых наблюдений с использованием высокоточных фазовых наблюдений, которые отличаютсяиспользованием дополнительных наблюдений – оценок прироста текущих координат подвижного объекта,полученные с прироста непрерывных фазовых наблюдений во времени. Такой подход реализовано с использованиеммодифицированного «leveling»–алгоритма сглаживания/фильтрации кодовых наблюдений с использованиемнепрерывных фазовых наблюдений в режиме кинематической съемки, что позволяет существенно улучшить иполучить гладкое координатное решение, которое уменьшает вариации и скачки координат, вызванные изменениемрабочего созвездия спутников и соответственно геометрического фактора (GDOP).Предложенное решение позволяет существенно повысить точность позиционирования и получить гладкоекоординатное решение. Результаты экспериментов показали, что на базовых расстояниях ~50 км возможноеповышение точности позиционирования в несколько раз по сравнению с аналогами і стандартным кодовымдифференциальным решением.У статті представлені результати розробки і верифікації модифікованого алгоритму кодово-фазового зглажування/фільтрації диференціальних ГНСС спостережень в задачах кінематичного позиціонуваннярухомих об’єктів. Запропонований підхід базується на застосуванні згладжування/фільтрації в реальному часікодових спостережень з використанням високоточних фазових спостережень, які відрізняються використаннямдодаткових спостережень – оцінок приросту поточних координат рухомого об’єкту, отриманих з приростунеперервних фазових спостережень за часом. Такий підхід реалізовано з застосуванням модифікованого«leveling»–алгоритму зглажування/фільтрації кодових спостережень з використанням неперервних фазовихспостережень в режимі кінематичної зйомки, що дозволяє значно підвищити точність та дозволяє отриматигладке координатне рішення яке зменшує варіації і скачки координат, викликаних зміною робочого сузір’ясупутників і відповідними змінами геометричного фактору (GDOP).Запропоноване рішення дозволяє значно підвищити точність позиціонування та отримати гладке координатнерішення. Результати експериментів показали, що на базових відстанях ~50 км можливе підвищення точностіпозиціонування в декілька раз в порівнянні з аналогами і стандартним кодовим диференціальним рішенням

An Artificial Neural Network Embedded Position and Orientation Determination Algorithm for Low Cost MEMS INS/GPS Integrated Sensors

Digital mobile mapping, which integrates digital imaging with direct geo-referencing, has developed rapidly over the past fifteen years. Direct geo-referencing is the determination of the time-variable position and orientation parameters for a mobile digital imager. The most common technologies used for this purpose today are satellite positioning using Global Positioning System (GPS) and Inertial Navigation System (INS) using an Inertial Measurement Unit (IMU). They are usually integrated in such a way that the GPS receiver is the main position sensor, while the IMU is the main orientation sensor. The Kalman Filter (KF) is considered as the optimal estimation tool for real-time INS/GPS integrated kinematic position and orientation determination. An intelligent hybrid scheme consisting of an Artificial Neural Network (ANN) and KF has been proposed to overcome the limitations of KF and to improve the performance of the INS/GPS integrated system in previous studies. However, the accuracy requirements of general mobile mapping applications can’t be achieved easily, even by the use of the ANN-KF scheme. Therefore, this study proposes an intelligent position and orientation determination scheme that embeds ANN with conventional Rauch-Tung-Striebel (RTS) smoother to improve the overall accuracy of a MEMS INS/GPS integrated system in post-mission mode. By combining the Micro Electro Mechanical Systems (MEMS) INS/GPS integrated system and the intelligent ANN-RTS smoother scheme proposed in this study, a cheaper but still reasonably accurate position and orientation determination scheme can be anticipated

Sparse 3D Point-cloud Map Upsampling and Noise Removal as a vSLAM Post-processing Step: Experimental Evaluation

The monocular vision-based simultaneous localization and mapping (vSLAM) is one of the most challenging problem in mobile robotics and computer vision. In this work we study the post-processing techniques applied to sparse 3D point-cloud maps, obtained by feature-based vSLAM algorithms. Map post-processing is split into 2 major steps: 1) noise and outlier removal and 2) upsampling. We evaluate different combinations of known algorithms for outlier removing and upsampling on datasets of real indoor and outdoor environments and identify the most promising combination. We further use it to convert a point-cloud map, obtained by the real UAV performing indoor flight to 3D voxel grid (octo-map) potentially suitable for path planning.Comment: 10 pages, 4 figures, camera-ready version of paper for "The 3rd International Conference on Interactive Collaborative Robotics (ICR 2018)