<?xml version="1.0" encoding="UTF-8"?><ns2:project xmlns:ns1="http://gtr.rcuk.ac.uk/gtr/api" xmlns:ns2="http://gtr.rcuk.ac.uk/gtr/api/project" xmlns:ns3="http://gtr.rcuk.ac.uk/gtr/api/fund" xmlns:ns4="http://gtr.rcuk.ac.uk/gtr/api/person" xmlns:ns5="http://gtr.rcuk.ac.uk/gtr/api/project/outcome" xmlns:ns6="http://gtr.rcuk.ac.uk/gtr/api/organisation" ns1:created="2026-06-03T15:52:43Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/97CF4C52-9CC6-4F93-8F1E-59AB400171AC" ns1:id="97CF4C52-9CC6-4F93-8F1E-59AB400171AC"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/39B28ACA-05A8-483E-9793-D03D60318DE4" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/DEBEE78C-5F54-4349-B8EF-E7673EEF1637" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/92AA8BD3-DC43-4AAE-B882-0ECD1B6C9B34" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/DEBEE78C-5F54-4349-B8EF-E7673EEF1637" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2014-09-29T23:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/5A775631-AB11-4A6C-AD58-B8F7DA6C6C7F" ns1:rel="FUND" ns1:start="2013-08-31T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">131291</ns2:identifier></ns2:identifiers><ns2:title>SmartBoomerang - Teach, Blog and Repeat for an Inspection Flying Robot</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Feasibility Studies</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>This project develops an autonomous path following capability (in the form of a sensor and algorithm kit) for aerial inspection robots used to remotely survey structures in sectors such as oil &amp;amp; gas, mining, energy, chemical processing, water and transport. Aerial robots have enormous potential to slash costs relative to manual inspections, which are equipment and manpower intensive and typically represent a large proportion of the recurring cost of a structure over its lifetime. Current generation robots are typically operated manually within line of sight of a remote operator; this project will develop a sensor and algorithm kit enabling such robots to automatically retrace their steps around a known structure using vision and learning, greatly speeding up repetitive surveys. A 3D visual feature map is generated and refined, and over subsequent missions a robot would use this map of the structure for autonomous visual navigation using a relocalisation approach, allowing it to reach and return from the areas to be inspected autonomously. The proposed robot combines the real-time full 3D visual mapping and relocalisation methods developed at the University of Bristol and flight control technology developed by Blue Bear.</ns2:abstractText></ns2:project>