Acoustic real-time, low-power FPGA based obstacle detection for AUVs

S. Karabchevsky, D. Kahana, H. Guterman

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

The underwater robots called Unmanned Underwater Vehicles (UUVs) take over complex and dangerous underwater missions that were previously performed by humans. These vehicles operate in the unknown environments and make their own decisions within the mission based on the readings of the sensors, without any link with a human operator. Independent of the mission, it is critical for the AUVs to be able to avoid submerged obstacles such as cliffs, wrecks, and floating mines. The AUV typically uses underwater imaging sonar that has several drawbacks for obstacle detection purposes, and therefore requires complex image processing algorithms. Due to the imaging sonar limitations, addressing obstacle detection using conventional software algorithms cannot meet an AUV's real-time, low power requirements. A low-power FPGA algorithm for underwater obstacle detection that is based on local image histogram entropy is proposed. The algorithm maintains a real-time reliable performance while meeting the AUV low power budget.

Original languageEnglish
Title of host publication2010 IEEE 26th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2010
Pages655-659
Number of pages5
DOIs
StatePublished - 1 Dec 2010
Event2010 IEEE 26th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2010 - Eilat, Israel
Duration: 17 Nov 201020 Nov 2010

Publication series

Name2010 IEEE 26th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2010

Conference

Conference2010 IEEE 26th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2010
Country/TerritoryIsrael
CityEilat
Period17/11/1020/11/10

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Acoustic real-time, low-power FPGA based obstacle detection for AUVs'. Together they form a unique fingerprint.

Cite this