Underwater crime scene investigation and emergency response are tasks typically carried out by divers constituting part of a specialist team. Operating in such dynamic environments, often with poor visibility and risk of concealed hazards, can be time consuming and dangerous. Autonomous uncrewed vessels with underwater acoustic imaging sensors have been used for similar purposes in other fields (e.g., hydrography, naval mine countermeasures [MCMS], etc.) but have not been adopted in this specific application domain. The Police Robot for Inspection and Mapping of underwater Evidence (PRIME) is an autonomous uncrewed surface vessel that is being developed for this purpose. It is a novel application of existing robotic technology that is intended to be used within an end-to-end police and emergency underwater search process. It aims to enhance the effectiveness, efficiency, and safety of divers by autonomously locating and highlighting target objects or regions of interest, as well as benign regions, thereby reducing their time spent underwater. Side-scan imaging sonars are used to sense the underwater environment using techniques leveraged from the similar application domain of naval MCMs. The system autonomously generates actionable intelligence in the form of simplified coverage and anomaly maps for easy interpretation by the dive team. These are communicated to shore in real-time and georeferenced on satellite maps. This paper details the PRIME system prototype and presents results from initial field experimentation. The prototype has been operated in various urban, shallow-water environments. The experimental results shown here were collected in Bristol Harbour (the UK) with a water depth of approximately 5 m. In the experiment, a clothed mannequin resembling a human body was deployed on the muddy floor. Autonomous searches were executed and the body was detected successfully as an anomaly against the background, illustrating the feasibility and viability of the system as an autonomous robotic aid for locating missing persons in a representative, unstructured, and dynamic real-world environment.

Original languageEnglish
Pages (from-to)983-1002
Number of pages20
JournalJournal of Field Robotics
Issue number5
Early online date21 Feb 2023
Publication statusPublished - 1 Aug 2023

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.


  • field robotics
  • search and rescue robots
  • sensing

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications


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