Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2022-06-06 Cooperative journals: 《计算机应用研究》
Abstract： In order to improve the estimation accuracy of the road slope during the movement of the robot, this paper proposed a fusion slope estimation algorithm for RGB-D(red green blue-depth) moving robot. Firstly, the method used random sampling consistency algorithm to complete the point cloud processing. Secondly, the normal vector estimation followed an improve plane fitting method. Finally, the cosine clustering and cumulative average method were used to accurately complete the road slope estimation. Experimental results showed that compared with the least squares method and the sparse subspace method under the data set, the estimation error of the algorithm is reduced by 1.21% and 2.13% respectively, in the actual environment, the average error is reduced by 1.43�compared with the least squares method, which verifies the feasibility and effectiveness of the proposed algorithm.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2022-04-07 Cooperative journals: 《计算机应用研究》
Abstract： This paper proposed a new network framework for RGB-D salient object detection (SR-Net) . In order to effectively integrate the complementarity of multi-model features, this paper took the depth feature extraction as an independent branch, use the Convolutional Block Attention Module(CBAM) to enhance the depth feature, and integrate the complementary information of the enhanced depth feature and RGB feature. Then, in order to remove feature redundancy and reduce the interference of background noise on the prediction results, it proposed a sequential refining network in the up-sampling network, that is, first, the primary global features are obtained by integrating the complementarity of multi-level and multi-scale features, and used the Primary Global Feature Weight Matrix Acquisition Module (PFW) which based on the channel weight to obtains the weight matrix of the primary global feature, and then uses the obtained weight matrix to refine the features of each level to suppress the interference which caused by background noise. Finally, in order to better optimize the whole network, it proposed a new loss function. The experimental results on four public datasets show that the model is superior to nine advanced methods in different model evaluation indexes, and achieves more advanced performance.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-08-13 Cooperative journals: 《计算机应用研究》
Abstract： Currently the visual SLAM system can only output the camera's motion trajectory, but it cannot generate maps for path planning and navigation. In order to solve this problem, this paper proposes a real-time grid map algorithm based on ORB-SLAM2. Firstly, 爐he爌aper establishes an inverse sensor model (ISM) for visual SLAM. 燬econdly, 爐he paper rearranges the construction mechanism of the grid map algorithm for ISM model and then derives it in detail. Finally, the paper introduces the specific implementation scheme of ORB-SLAM2 grid map construction. Through experiments, the algorithm shows its feasibility based on the analysis of the ISM model and the grid map model. Furthermore, the real-time experiments using monocular camera and RGB-D camera can realize爐he real-time construction of the grid map and clearly show the positions of obstacles, which verifies the effectiveness of the algorithm.
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