Model shape oriented robust matching of dot cloud data based and its application to defect recognition

Kayaba, Hiroyuki; Takauji, Hidenori; Kaneko, Shun’ichi; Toda, Masataka; Kuno, Kouji; Suganuma, Hiroyuki

doi:10.1109/isot.2010.5687364

Search citation statements

Order By: Relevance

Paper Sections

Select...

A Accuracy: Increasing Precision Of the Iterative1

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2023

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

(1 citation statement)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Closest Point Authors [3] extend M-ICP [4], which comprehensively matches 3D shapes to outlying data (that is, including nonoverlapping data or unexpected noise), and present an advanced example of a remarkably efficient and precise method for measuring complex 3D shapes with steep surfaces.…”

Section: A Accuracy: Increasing Precision Of the Iterativementioning

confidence: 99%

Latest Trends in Visual Manipulation and Navigation in Robotics

Amri

Areche

Naik

2023

JNEST

View full text Add to dashboard Cite

In recent decades, the term Robot has become more and more popular. A robot can be defined as a machine that is specifically built to complete certain tasks to help human-being. In order to successfully accomplish its task, the robot needs to receive input data and process it. Then, the processed data is used for manipulator-actions decision-making. The input data can vary from sound, temperature, vibration, touch, vision, etc. Among those input data, vision is arguably one of the most challenging data. This is because vision often needs detailed and complicated preprocessing before it can be used. In addition, vision data size is relatively larger compared to the other type of input data, making it more challenging to process considering the computational resources. In this paper, current research and future development trend of robotic vision were reviewed and discussed. Further, challenges and potential issues about robot vision, such as safety and privacy concerns, were also discussed.

show abstract

Section: A Accuracy: Increasing Precision Of the Iterativementioning

confidence: 99%