2023 Vol.6 Dec.N06

• Title: Dynamic Target Detection for DJI Robots Based on Semantic Segmentation
• Name: XiaoHeng123
• Company: (1.School of Information & Intelligence Engineering, University of Sanya, Sanya, 572022, China (2.Academician Guoliang Chen Team Innovation Center, University of Sanya, Sanya, 572022, China (3.Academician Chunming Rong Workstation, University of Sa
• Abstract:

  Current conventional robotic dynamic target detection algorithms mainly extract key point features by fusing point cloud data, which leads to poor detection results due to the lack of modeling processing of the target region. In this regard, a dynamic target detection method for DJI robot based on semantic segmentation is proposed. First, a semantic target database is established to update the target object information, and the semantic information of the database is fused with the point cloud map to obtain a globally consistent semantic map. And the dynamic window modeling is realized by establishing the velocity vector space. Finally, the dynamic target detection network structure is optimized by combining the PANet multi-scale feature fusion method. In the experiments, the detection effect of the proposed method is verified. Finally, the experimental comparison results can prove that the algorithm has a higher detection accuracy and more ideal detection effect when the proposed method is used for dynamic target detection.

  
  

• Keyword: semantic segmentation; robotics; dynamic targets; detection algorithms;
• DOI: 10.12250/jpciams2023090817
• Citation form: XiaoHeng.Dynamic Target Detection for DJI Robots Based on Semantic Segmentation [J]. Computer Informatization and Mechanical System,2023,Vol.6,pp.81-85

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