Deep Learning-Based Connector Detection for Robotized Assembly of Automotive Wire Harnesses
Paper i proceeding, 2023

The shift towards electrification and autonomous driving in the automotive industry results in more and more automotive wire harnesses being installed in modern automobiles, which stresses the great significance of guaranteeing the quality of automotive wire harness assembly. The mating of connectors is essential in the final assembly of automotive wire harnesses due to the importance of connectors on wire harness connection and signal transmission. However, the current manual operation of mating connectors leads to severe problems regarding assembly quality and ergonomics, where the robotized assembly has been considered, and different vision-based solutions have been proposed to facilitate a better perception of the robot control system on connectors. Nonetheless, there has been a lack of deep learning-based solutions for detecting automotive wire harness connectors in previous literature. This paper presents a deep learning-based connector detection for robotized automotive wire harness assembly. A dataset of twenty automotive wire harness connectors was created to train and evaluate a two-stage and a one-stage object detection model, respectively. The experiment results indicate the effectiveness of deep learning-based connector detection for automotive wire harness assembly but are limited by the design of the exteriors of connectors.

Författare

Hao Wang

Chalmers, Industri- och materialvetenskap, Produktionssystem

Björn Johansson

Chalmers, Industri- och materialvetenskap, Produktionssystem

IEEE International Conference on Automation Science and Engineering

21618070 (ISSN) 21618089 (eISSN)

Vol. 2023-August
9798350320695 (ISBN)

19th IEEE International Conference on Automation Science and Engineering, CASE 2023
Auckland, New Zealand,

EWASS Empowering Human Workers for Assembly of Wire Harnesses

VINNOVA (2022-01279), 2022-07-01 -- 2025-05-31.

Ämneskategorier

Datorteknik

Produktionsteknik, arbetsvetenskap och ergonomi

Robotteknik och automation

Annan elektroteknik och elektronik

DOI

10.1109/CASE56687.2023.10260619

Mer information

Senast uppdaterat

2023-11-06