<?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="2026-08-26T13:36:10Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/923BE540-733C-420D-A7AA-0AC845682603" ns1:id="923BE540-733C-420D-A7AA-0AC845682603"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/FAE11A75-27CB-4137-8521-E1E676749B47" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/8A9BD3E8-81C2-4E90-AF4F-2AFDB13327F7" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/BFE41CB6-4B8A-4082-B96B-3DFEFE793924" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/8A9BD3E8-81C2-4E90-AF4F-2AFDB13327F7" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2020-11-30T00:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/12476826-2A23-4CD1-A243-D52F6F6FA93C" ns1:rel="FUND" ns1:start="2019-03-01T00:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">105016</ns2:identifier></ns2:identifiers><ns2:title>Translating Advanced Camera Tracking Technology to High Precision and High Reliability Indoor Navigation Sensing Enabling More Applications for the Growing Robotics Market</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Feasibility Studies</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>&amp;quot;Mobile robotics have already changed the face of industry. By moving materials and products in an automated manner, they offer efficient and cost-effective ways to store and manage the flow of products through many industrial activities.

Automated Guided Vehicles (AGVs) are used for this purpose with minimal human intervention. Amazon, in particular, are using AGVs extensively within its warehouses to speed-up the collection and shipping of goods.

However, to be able to carry this out well, the robots must know where they are (localisation), where they need to go, and to move in such a way that the materials are safely transported and are not damaged (control). AGVs use a range of guidance systems to do this. These range from simple wire, tape, or magnetic systems to more complex inertial, laser target, or Simultaneous Localisation And Mapping (SLAM) systems.

For simple, repetitive motions, and for open environments that remain largely unchanged, wire/tape and other guidance solutions are usually adequate. However, where the factory environment is difficult (e.g. complex pipework) or when high-precision is required for coupling/joining of containers or parts, and particularly in safety-critical environments with dangerous chemicals, most current AGV solutions fall short in terms of accuracy, reliability, and functionality.

Mo-Sys has developed a world-leading camera positioning and tracking system for use in the media industries. &amp;quot;&amp;quot;StarTracker&amp;quot;&amp;quot; is an upwards looking visual sensor that orientates itself relative to randomly applied reflective stickers. The method is matured, patented and used for over three years in TV green screen studios. It is robust, immune to contrast changes, and can work in darkness.

It is the intention of this project to develop this technology, primarily in the areas of accuracy and control, for AGV applications. It would not require any floor-based guiding systems or laser scanners that try to recognise a position within a dynamically changing environment. Once the stickers are on the ceiling, all objects refer to the same world and can collaborate in a smart factory. StarTracker would be able to guide an AGV robustly and precisely within an unlimited indoor area.

Aside from benefits in cost, time, and productivity for the relevant industries, it would have numerous wider benefits in terms of reducing human error, increasing safety in hazardous environments, and removing humans from monotonous tasks in to more value-added activity. The technology also has the potential to trickle-down in to healthcare, domestic and other robotic applications.&amp;quot;</ns2:abstractText></ns2:project>