急峻な動き特徴と空間重要度に基づく3次元バレーボール解析向け自動データ取得手法

早大学位記番号:新7922早稲田大

A Bidirectional Scoring Strategy-Based Transformation Matrix Estimation of Dynamic Factors in Environmental Sensing

Simultaneous localization and mapping (SLAM) is the technological basis of environmental sensing, and it has been widely applied to autonomous navigation. In combination with deep learning methods, dynamic SLAM algorithms have emerged to provide a certain stability and accuracy in dynamic scenes. However, the robustness and accuracy of existing dynamic SLAM algorithms are relatively low in dynamic scenes, and their performance is affected by potential dynamic objects and fast-moving dynamic objects. To solve the positioning interference caused by these dynamic objects, this study proposes a geometric constraint algorithm that utilizes a bidirectional scoring strategy for the estimation of a transformation matrix. First, a geometric constraint function is defined according to the Euclidean distance between corresponding feature points and the average distance of the corresponding edges. This function serves as the basis for determining abnormal scores for feature points. By utilizing these abnormal score values, the system can identify and eliminate highly dynamic feature points. Then, a transformation matrix estimation based on the filtered feature points is adopted to remove more outliers, and a function for evaluating the similarity of key points in two images is optimized during this process. Experiments were performed based on the TUM dynamic target dataset and Bonn RGB-D dynamic dataset, and the results showed that the added dynamic detection method effectively improved the performance compared to state of the art in highly dynamic scenarios

A Literature Review and Result Interpretation of the System Identification of Arch Dams Using Seismic Monitoring Data

The system identification of concrete dams using seismic monitoring data can reveal the practical dynamic properties of structures during earthquakes and provide valuable information for the analysis of structural seismic response, finite element model calibration, and the assessment of postearthquake structural damage. In this investigation, seismic monitoring data of the Pacoima arch dam were used to identify the structural modal parameters. The identified modal parameters of the Pacoima arch dam, derived in different previous studies that used forced vibration tests (FVT), numerical calculation, and seismic monitoring, were compared. Meanwhile, different modal identification results using the input-output (IO) methods and the output-only (OO) identification methods as well as the linear time-varying (LTV) modal identification method were adopted to compare the modal identification results. Taking into account the different excitation, seismic input, and modal identification methods, the reasons for the differences among these identification results were analyzed, and some existing problems in the current modal identification of concrete dams are pointed out. These analysis results provide valuable guidance regarding the selection of appropriate identification methods and the evaluation of the system identification results for practical engineering applications