Search

The flatness error is one of the critical parameters of a circular saw, which seriously affects the cutting performance. In this paper, the measurement of the circular saw flatness error based on a laser displacement sensor is proposed. For the tooth of a circular saw, the plane is discontinuous. According to the field detection demand of a circular saw, the authors collected Archimedean spiral three coordinate data of the circular saw using a laser displacement sensor. Considering the practical application of circular saw flatness detection, the authors have established an ideal plane model of the flatness based on the least‐squares method to evaluate the flatness error of circular saws. The system has a maximum detection area of 400 mm × 400 mm, the measurement time is 80 s, and the measurement absolution accuracy is 10 μm. [ABSTRACT FROM AUTHOR]

LiDAR matching between real-time point clouds and pre-built points map is a popular approach to provide accurate localisation service for autonomous vehicles. However, the performance is severely deteriorated in dense traffic scenes. Unavoidably, dynamic vehicles introduce additional uncertainty to the matching result. The main cause is that the pre-built map can be blocked by the surrounding dynamic vehicles from the view of LiDAR of ego vehicle. A novel uncertainty of LiDAR matching (ULM) estimation method aided by the dynamic vehicle (DV) detection and high definition map is proposed in this Letter. Compared to the conventional Hessian matrix-based ULM estimation approach, the proposed method innovatively estimates the ULM by modelling surrounding DV. Then the authors propose to correlate the ULM with the detected DV and convergence feature of matching algorithm. From the evaluated real-data in an intersection area with dense traffic, the proposed method has exhibited the feasibility of estimating the ULM accurately. [ABSTRACT FROM AUTHOR]