Autonomous traction control for the intelligent excavator system

Sun Im, Seung Yun Choi, Jong Bae Lee

Research output: Contribution to conferencePaper

6 Citations (Scopus)

Abstract

With the recent development of information technology (IT), automation is being introduced in the construction sites as well as in plants. This study was conducted to address autonomous driving in the outside environment as part of the construction automation task in the advanced fusion construction research project of the Ministry of Land, Transport, and Maritime Affairs. The DGPS and IMU sensor were used to acquire the position and posture information of the excavator in the outside environment, and the information was used to create and follow diverse movement trajectories and to ensure smooth autonomous excavation. For autonomous driving, a vehicle-type control device, which was named remote control station (RCS), and an excavator attribute-sensing module, which was mounted on the excavator, were developed. The excavator attribute-sensing module was mounted on the electrohydraulic excavator, which allowed the wireless communication of the excavator state between the excavator and the mobile control station and autonomous driving. The path-tracking and posture control algorithm for the excavator that had no additional steering system for the outside environment, which was proposed in this study, significantly differs from that of the conventional and general mobile platform in the inside/outside environment. The precision and reliability of the proposed autonomous control algorithm was verified via diverse tests in the actual environment.

Original languageEnglish
Pages1440-1444
Number of pages5
Publication statusPublished - 2011
Externally publishedYes
Event28th International Symposium on Automation and Robotics in Construction, ISARC 2011 - Seoul, Korea, Republic of
Duration: 2011 Jun 292011 Jul 2

Other

Other28th International Symposium on Automation and Robotics in Construction, ISARC 2011
CountryKorea, Republic of
CitySeoul
Period11/6/2911/7/2

Keywords

  • Autonomous traction control
  • Excavator
  • Intelligent excavator system

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Building and Construction

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