返回
Object pose estimation for robot loading in accommodation space using alpha-shape algorithm
DOI:10.1007/s00500-021-06237-8.png)
摘要
En 中文
Robots with visual sensors have been used in various goods logistics, such as bin picking or uploading. However, there are more and more demands for the automatic blanking and loading, and it is necessary to solve the problem of object pose estimation in changing accommodation space. This paper proposes a method for pose estimation in the accommodation space using alpha-shape algorithm and improved fruit fly optimization algorithm (FOA). The alpha-shape volume variety of object and measured space is set to the objective function, and the pose variety of object is set to six variables of improved FOA. The experiments were performed by setting parameters of improved FOA and considering the four space types represented the common accommodation shapes. Compared with previous work using convex hull, the new study using alpha-shape algorithm not only keeps the object in the accommodation space, but also maintains the object pose which is at the bottom of the space and can meet the practical requirement of object placement by robot arms.
Keyword:
Robot
Pose estimation
Alpha-shape algorithm
Fruit fly optimization
Accommodation space
AI总结
对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
2.5
论文数:
1.0W
被引数:
2.1W
机构
引用论文
Application of the morphological alpha shape method to the extraction of topographical features from engineering surfaces
MEASUREMENT
IF5.6
A new Fruit Fly Optimization Algorithm: Taking the financial distress model as an example一种新的果蝇优化算法 -- 以财务困境模型为例
Drought and Desalination: Melbourne water supply and development choices in the twenty-first century干旱和海水淡化: 21世纪墨尔本的供水和发展选择

