一种基于点云的机械手抓取方法  

A Grasping Method of Manipulator Based on Point Cloud

作　　者：张自杰 张国良 曾静 汪坤 李德胜 王艺成 ZHANG Zijie;ZHANG Guoliang;ZENG Jing;WANG Kun;LI Desheng;WANG Yicheng(School of Automation and Information Engineering,Sichuan University of Science&Engineering,Yibin Sichuan 644000,China;Artificial Intelligence Key Laboratory of Sichuan Province,Yibin Sichuan 644000,China)

机构地区：[1]四川轻化工大学自动化与信息工程学院,四川宜宾644000 [2]人工智能四川省重点实验室,四川宜宾644000

出　　处：《机床与液压》2023年第15期76-82,共7页Machine Tool & Hydraulics

基　　金：四川省应用基础研究项目(2019YJ00413)。

摘　　要：针对传统的机械手抓取方法难以获得可靠抓取位姿的问题,提出一种基于点云的抓取方法。通过深度相机获得工作空间的部分点云;采用GPD法在点云空间采样候选抓取位姿;最后,通过自主设计的评估模型筛选出高质量的抓取位姿。基于所提方法,搭建了完整的自主抓取系统,对多种物体进行实际抓取实验。结果表明:算法能有效地检测出可靠的抓取位姿,且对未知物体的泛化性良好,抓取成功率和抓取完成度较传统方法有明显提升,能够满足各类抓取任务的需求。To solve the problem that traditional grasping methods of manipulator are difficult to obtain reliable grasping poses,a new grasping algorithm based on point cloud was presented.The partial point cloud of work space was captured by depth camera.The candidate grasping poses were sampled over point cloud space using GPD method.Finally,a grasping pose with high quality was selected by self-designed evaluation model.A complete autonomous grasping system was built based on proposed method,and grasping experiments were conducted to a variety of objects.The results show that the proposed algorithm can effectively detect reliable grasping poses and generalize well to novel objects,the grasping successful rate and completion degree are improved than traditional algorithms and it is able to meet the needs of various grasping tasks.

关 键 词：点云 GPD法 抓取位姿 自主抓取 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]