赵新灿, 展鹏磊, 吴飞, 张大伟. 基于领域知识的3维动态场景目标识别和配准[J]. 机器人, 2018, 40(4): 534-539. DOI: 10.13973/j.cnki.robot.180099
引用本文: 赵新灿, 展鹏磊, 吴飞, 张大伟. 基于领域知识的3维动态场景目标识别和配准[J]. 机器人, 2018, 40(4): 534-539. DOI: 10.13973/j.cnki.robot.180099
ZHAO Xincan, ZHAN Penglei, WU Fei, ZHANG Dawei. Target Recognition and Registration in 3D Dynamic Scene Based on Domain Knowledge[J]. ROBOT, 2018, 40(4): 534-539. DOI: 10.13973/j.cnki.robot.180099
Citation: ZHAO Xincan, ZHAN Penglei, WU Fei, ZHANG Dawei. Target Recognition and Registration in 3D Dynamic Scene Based on Domain Knowledge[J]. ROBOT, 2018, 40(4): 534-539. DOI: 10.13973/j.cnki.robot.180099

基于领域知识的3维动态场景目标识别和配准

Target Recognition and Registration in 3D Dynamic Scene Based on Domain Knowledge

  • 摘要: 为了增强遥操作系统的临场感,使操作者更好地融入远程工作环境,提出了基于领域知识的3维动态场景目标识别和配准算法.首先,通过离线解析和切分虚拟样机CAD(计算机辅助设计)模型构建包含多视角点云特征和装配约束的领域知识库.其次,通过动态采集场景点云并计算CVFH(clustered viewpoint feature histogram)和FPFH(fast point feature histogram)特征,利用领域知识库中多视角点云特征和点云CVFH特征进行比对实现目标识别,并由FPFH特征经过两步配准实现目标姿态确定.最后,利用装配约束知识库实现以遥操作机器人工作状态变化为驱动的指导信息的精确配准和实时推送.实验结果表明,该系统不但可以有效地指导远程机器人完成维修操作,还可以提高遥操作的精度和效率.

     

    Abstract: A target recognition and registration algorithm based on domain knowledge in 3-dimensional dynamic scene is proposed to enhance the sensory immersion of the teleoperation system and make the operator better integrate into the remote working environment. Firstly, a domain knowledge database containing multi-view point cloud features and assembly constraints is constructed by offline parsing and segmentation of virtual prototype CAD (computer aided design) models. Then, the CVFH (clustered viewpoint feature histogram) and FPFH (fast point feature histogram) features are computed by dynamically collecting scene point clouds, and the multi-view point cloud features contained in domain knowledge database and the CVFH features are compared to implement target recognition. The target pose is obtained using the FPFH features through two-step registration. Finally, the accurate registration and real-time push of guidance information driven by the changes of working state of the teleoperation robot are implemented using the assembly constraint knowledge database. The experimental results show that the algorithm can not only effectively guide the remote robot to complete the maintenance operation, but also improve the precision and efficiency of teleoperation.

     

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