Stand-off Underwater iDentification by Operator of auto-Classified Objects (SUDOCO)

Abstract

Stand-off Mine Counter-Measure (MCM) operations with unmanned systems frequently require user involvement for the interpretation of image data (for classification and identification) and for decision-making during mine disposal. The latter even requiring tethering , leading to cumbersome operating procedures. TNO proposes the development and demonstration of a high-bandwidth and Quality-of-Serv ice (QoS) enabled acoustic data link for communication of live images and meta data from untethered underwater systems to an operato r. Novel is the application of QoS diversity principles to the transmission of single messages with both live MCM image data and met a data to operators using wireless acoustic communication signals. The meta data, being high-priority low-volume data such as the sy stems position, course and speed, as well as object classification/localization results, are communicated with high reliability on top of the image data that itself may allow some errors (e.g., bad pixels) to remain useful for the operator. For demonstration of t he concept, TNO has full control over an Autonomous Underwater Vehicle (AUV), i.e., the sensor processing unit and the software-defi ned modem, where the latter covers a 21-kHz bandwidth transducer (carrier @31.5 kHz; data rate ~4 kb/s). The described capability ma y be demonstrated at REPMUS21 using an AUV equipped with an optical camera and a side-looking sonar (SLS).

Document Details

Document Type
DoD Grant Award
Publication Date
Sep 07, 2021
Source ID
N629092112060

Entities

People

  • Henry Dol

Organizations

  • Netherlands Organisation for Applied Scientific Research
  • Office of Naval Research
  • United States Navy

Tags

Readers

  • Computer Vision.
  • Distributed Systems and Data Platform Development
  • Unmanned Aerial System (UAS) Autonomous Capabilities and Mission Reconnaissance.

Technology Areas

  • Autonomy