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Autonomous Driving of Six-Wheeled Dump Truck with Retrofitted Robot

EasyChair Preprint 1506

14 pagesDate: September 12, 2019

Abstract

In Japan, expectations for the automation of construction machines are increasing to solve labor shortage in the construction industry. In this research, a robotization method by retrofitting a robot to conventional construction machines is introduced to lower the introduction barrier for regional construction companies. The target machine is a six-wheeled dump truck. With a retrofitted internal sensor unit and derived kinematics of six-wheeled articulated dump truck, a conventional GNSS-based path tracking method was implemented on it. In addition, to ensure safety during operation, an emergency stop function was installed on the dump truck with three dimensional Light Detection and Ranging (3D-LiDAR). Initial experiments of forward and backward path tracking with actual dump truck confirmed the validity of the method, and the maximum tracking error was 1 m. Further, in an emergency stop experiment, the dump truck detected the obstacle and stopped immediately after obstacle detection within the emergency-stop region, i.e., 25 m x 3 m in front of the dump truck. Based on the initial experiments, the authors concluded that even the retrofitted conventional dump truck could perform basic functions for autonomous driving, such as path tracking and emergency stop.

Keyphrases: Autonomous construction machinery, Path Tracking Control, Six-Wheeled dump truck kinematics, obstacle detection, pneumatic robot

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@booklet{EasyChair:1506,
  author    = {Tomohiro Komatsu and Yota Konno and Seiga Kiribayashi and Keiji Nagatani and Takahiro Suzuki and Kazunori Ohno and Taro Suzuki and Naoto Miyamoto and Yukinori Shibata and Kimitaka Asano},
  title     = {Autonomous Driving of Six-Wheeled Dump Truck with Retrofitted Robot},
  howpublished = {EasyChair Preprint 1506},
  year      = {EasyChair, 2019}}
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