Currently, digital maps are indispensable for automated driving. However, due to the low precision and reliability of GNSS particularly in urban areas, fusing trajectories of independent recording sessions and different regions is a challenging task. To bypass the flaws from direct incorporation of GNSS measurements for geo-referencing, the usage of aerial imagery seems promising. Furthermore, more accurate georeferencing improves the global map accuracy and allows to estimate the sensor calibration error. In this paper, we present a novel geo-referencing approach to align trajectories to aerial imagery using poles and road markings. To match extracted features from sensor observations to aerial imagery landmarks robustly, a RANSAC-based matching approach is applied in a sliding window. For that, we assume that the trajectories are roughly referenced to the imagery which can be achieved by rough GNSS measurements from a low-cost GNSS receiver. Finally, we align the initial trajectories precisely to the aerial imagery by minimizing a geometric cost function comprising all determined matches. Evaluations performed on data recorded in Karlsruhe, Germany show that our algorithm yields trajectories which are accurately referenced to the used aerial imagery.
The fusion of motion data is key in the fields of robotic and automated driving. Most existing approaches are filter-based or pose-graph-based. By using filter-based approaches, parameters should be set very carefully and the motion data can usually only be fused in a time forward direction. Pose-graph-based approaches can fuse data in time forward and backward directions. However, pre-integration is needed by applying measurements from inertial measurement units. Additionally, both approaches only provide discrete fusion results. In this work, we address this problem and present a uniform B-spline-based continuous fusion approach, which can fuse motion measurements from an inertial measurement unit and pose data from other localization systems robustly, accurately and efficiently. In our continuous fusion approach, an axis-angle is applied as our rotation representation method and uniform B-spline as the back-end optimization base. Evaluation results performed on the real world data show that our approach provides accurate, robust and continuous fusion results, which again supports our continuous fusion concept.
a b s t r a c tThe effects of the molding pressure of a KO 2 oxygen plate and the initial concentration of CO 2 on the oxygen generation rate, the oxygen generation efficiency, and the carbon dioxide absorption rate were studied using a YES-300 hydraulic press to alter the pressure when forming the oxygen plate used in a coal mine refuge chamber. In addition, changes in the initial concentration of CO 2 used in the closedbox model were made by adjusting the CO 2 supply system, and a CD-7 multi-function parameter instrument was employed to monitor and record the changes of O 2 and CO 2 concentration in the closed-box model. Results indicate that the oxygen generation rate of KO 2 oxygen plates, the oxygen generation efficiency, and the carbon dioxide absorption rate decrease when there is an increase in the pressure used to mold the oxygen plates, but those values increase when the initial CO 2 concentration increases. When the initial concentration of CO 2 in the closed-box model is 3.5% and the forming pressure is 10 kN, the average oxygen generation rate of 15 g KO 2 oxygen plate is 11.88 Â 10 À3 L/min, the oxygen generation efficiency is 80.3%, and the average CO 2 absorption rate is 11.0 Â 10 À3 L/min. Compared with the condition where the initial CO 2 concentration is 1.5%, the results show that average oxygen generation rate of oxygen plates increases by 88.9%, the oxygen generation efficiency increases by 88.9%, and the CO 2 absorption rate increases by 100%.
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