工程科学与技术2025，Vol.57Issue(5)：298-308,11.DOI:10.12454/j.jsuese.202400426
面向无序分拣场景的工件6D位姿检测方法
A Method of 6D Pose Detection for Workpieces in Random Sorting Scene
摘要
Abstract
Objective 6D pose detection is a key technology for enabling autonomous grasping in robots.Currently,traditional point‒pair feature(PPF)meth-ods face three major challenges:1)excessive sensitivity to sensor noise,severe occlusions,and background clutter;2)reduced matching perfor-mance when the workpiece has numerous repetitive features;3)slow recognition speed due to the need to search many point pairs and compute transformation relationships.This study proposes a point-pair feature-based 6D pose detection method designed for robotic sorting system grasp-ing tasks. Methods Firstly,multi-plane feature workpieces were screened based on distributions of model plane points,and their boundary features were ex-tracted for 6D pose detection.Model point pairs were extracted from multi-view points to remove redundant point pairs and improve the recogni-tion speed of algorithms.Secondly,to further enhance recognition speed,a method was employed to extract model point pairs from multiple view-points,which helped in eliminating redundant point pairs that did not contribute to the detection process.Thirdly,the point-to-point characteris-tics between scenes and models were matched,and a fast voting scheme was employed to obtain pose hypothesis sets for targets in a disordered scene.Then,a pose verification and screening method was introduced to eliminate duplicate and mismatched poses,which was essential for real-izing a rough estimation of multi-instance poses for the targeted workpieces.Finally,an algorithm called Iterative Closest Points(ICPs)was uti-lized to refine the rough estimates and achieve a more accurate estimation of the targeted poses. Results and Discussions Experimental results showed that in the context of disordered simulation scenes,the proposed method demonstrated a single recognition time of £ 1.2 seconds,with an average translation deviation of £ 1 mm and an average rotation error of £ 1.56°.These results in-dicated a high level of precision and efficiency in pose detection.In an actual scenario,this method achieved an average recognition success rate of 95.8%,with an average single recognition time of 1.1 seconds.The high success rate and rapid speed highlighted that this method has favor-able practical applicability in robotic sorting tasks.Therefore,this study highlighted that the proposed 6D pose detection method significantly out-performed the original PPF algorithm in terms of recognition speed,while also improving the accuracy of pose estimation.This advancement was crucial for the reliable and efficient operation of robotic systems in precision grasping applications.Finally,this 6D pose detection method not only ensured recognition efficiency but also accounted for the accuracy of pose estimation.This meant that recognition speed was significantly improved compared to the original PPF algorithm,providing a strong guarantee for the realization of accurate robotic grasping. Conclusions The research presents a comprehensive approach to enhancing 6D pose detection in disordered sorting scenarios,representing a sig-nificant advancement in robotic vision and grasping technologies.The proposed method is verified as effective in both simulated environments and real-world working conditions.In addition,it demonstrates superior performance compared to existing approaches,supporting more accurate analysis in 6D pose detection applications.关键词
无序场景/6D位姿检测/点对特征/位姿估计精度/识别率Key words
disordered scene/6D pose detection/point-to-point feature/pose estimation accuracy/recognition rate分类
信息技术与安全科学引用本文复制引用
曹学鹏,李鑫,冯艳丽,石瑞,葛天烨,张新荣,赵睿英..面向无序分拣场景的工件6D位姿检测方法[J].工程科学与技术,2025,57(5):298-308,11.基金项目
国家自然科学基金项目(62073092) （62073092）
陕西省重点研发计划项目(2021ZDLGY09‒02 （）
2024GX‒YBXM‒164) （）
