Object pose estimation method for robot grasping process

LI Shuchun; ZHANG Jing; ZHANG Hua; LIU Manlu; YANG Houyi; LIU Lixiang

doi:10.13873/j.1000-9787(2019)07-0032-03

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Object pose estimation method for robot grasping process

更新时间：2025-09-11

- Object pose estimation method for robot grasping process
- Issue 7, Pages: 32-34+38(2019)
- 作者机构：
  
  1. 西南科技大学信息工程学院
  2. 中国科学技术大学信息科学技术学院
- 作者简介：
- 基金信息：
- DOI：10.13873/j.1000-9787(2019)07-0032-03
  CLC： TP242
- Published：2019
- 稿件说明：
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LI Shuchun, ZHANG Jing, ZHANG Hua, et al. Object pose estimation method for robot grasping process[J]. 2019, (7): 32-34+38.
DOI：

LI Shuchun, ZHANG Jing, ZHANG Hua, et al. Object pose estimation method for robot grasping process[J]. 2019, (7): 32-34+38. DOI： 10.13873/j.1000-9787(2019)07-0032-03.

摘要

针对机械臂抓取过程中场景的复杂性和存在遮挡问题

提出了一种基于深度相机的物体位姿估计方法。采用Kinect相机获取点云图像

提取点云的FPFH特征。采用奇异值分解算法和随机一致算法来进行位姿估计。将得到的位姿经过手眼转换转换为抓取位姿。通过与ICP算法和NDT算法进行对比实验

结果验证了该方法的稳定性和精确性。

Abstract

Aiming at the problem of complexity of the scene and occlusion during robot grasping

a object pose estimation method based on depth camera is proposed. Kinect camera is used to capture point cloud image. The FPFH features of point cloud is extracted. Singular value decomposition algorithm and random sample consensus（RANSAC） algorithm are used to estimate the pose of object. The obtained pose is converted into grab posture by hand-eye conversion. Comparing with ICP algorithm and NDT algorithm

the results verify the stability and accuracy of the method.

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