3D Irregular Object Recognition for Twist-lock Handling System
The handling of twist-locks has been a heavy burden for the container industry.There have been many efforts in developing automated twist-lock handling solutions.To address this challenge,we are developing a customized mobile manipulator for twist-lock grasping.The technical challenge is 3D irregular object recognition in unstructured port environment.In this paper,we use PCA and KPCA to do two-level object recognition only depending on depth information to determine the basic instance and pose information for twist-lock grasping.The extensive experiments are carried out to select the optimal recognition parameters,investigate the performance of PCA,KPCA and compare their performance.Since depth images are insensitive to changes in lighting conditions,the experimental results show that the proposed approach based on depth information is effective to address the issues and solve problems caused by rust and painting peeled off of twist-lock handling in unstructured port environment.
feature extraction 3D recognition PCA KPCA twist-lock handling
Shuang Ma Changjiu Zhou Liandong Zhang Wei Hong Yantao Tian
College of Communication Engineering,Jilin University,Changchun 130025,China;Advanced Robotics and I Advanced Robotics and Intelligent Control Centre,Singapore Polytechnic,500 Dover Road,139651,Singapo College of Communication Engineering,Jilin University,Changchun 130025,China
国际会议
长沙
英文
2729-2734
2014-05-31（万方平台首次上网日期，不代表论文的发表时间）