Heading control and shoreline detection for river navigation using autonomous surface vessel

Chee Sheng Tan, Rosmiwati Mohd-Mokhtar*, Mohd Rizal Arshad

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Heading control scheme and shoreline detection play a significant role to vision-based navigation system in riverine environment. In this paper, side-line heading and center-line heading control for an Autonomous Surface Vessel (ASV) that capable of maneuvering along the river are presented. The ASV is equipped with propeller and rudder to control the speed and heading direction, respectively. Continuous stream of images are captured by camera that mounted on ASV and sent to the base station over network in low latency. An image segmentation algorithm based on Hough Transform technique is implemented for waterline detection. The purpose of using Hough Transform is to perform visual based navigation that track along with the river. Besides, a high accuracy GPS receiver is installed on the ASV to provide the latitude and longitude coordinates. Proportional control is designed as heading controller in order to stabilize the unstable process. Data logger system helps to save the data and important information for further analysis and processing. The optical flow algorithm is implemented to detect and avoid obstacle. The ASV’s navigation, control and task specific vision have been evaluated through experiments with results presented to demonstrate its capabilities.

Original languageEnglish
Pages (from-to)2471-2481
Number of pages11
JournalIndian Journal of Geo-Marine Sciences
Volume46
Issue number12
Publication statusPublished - Dec 2017
Externally publishedYes

Keywords

  • Autonomous surface vessel (ASV)
  • Heading control scheme
  • Hough transform
  • Image segmentation
  • Shoreline detection

Fingerprint

Dive into the research topics of 'Heading control and shoreline detection for river navigation using autonomous surface vessel'. Together they form a unique fingerprint.

Cite this