1. To develop Frequency Scanning Interferometry (FSI)-based techniques with high-performance data analysis capable of: (i) tracking at least 3 targets at speeds of up to 150 mm/s with quantified position uncertainty; (ii) updating data at a rate of 100 Hz to enable input to closed-loop 6DoF robotic controls for trajectory correction; (iii) reducing latency of the processing electronics / algorithms to a minimum.
  2. To develop low-cost photogrammetry-based metrology systems for very large volumes with elevated dynamic capability (up to 10 m/s) and high frame rate (> 100 Hz) capable of:
    (i) tracking large numbers of mobile entities (g. AGVs, drones and mobile robots) across the entire factory; (ii) allowing adaptive real time synchronization of virtualised and real factories for cloud-based coordination of complex automation systems.
  3. To design and produce (a) an IoT-based architecture to integrate cooperative LVM systems with reconfigurable, self-automating processes in the FoF. The architecture should: (i) integrate methods for tracking data integrity in addition to conventional traceability; (ii) include uncertainty models for dynamic coordinate measurements for automated assignment of metrology resources to dynamic automation platforms (g. robots); (iii) provide a framework for deducing communication requirements (latency, bandwidth) from metrology based cyber physical manufacturing systems; and (b) automated, dynamic reconfiguration of distributed LVM systems capable of reacting to the visibility and uncertainty constraints of factory environments.
  4. To develop equipment, models and associated strategies for dynamic performance evaluation/error compensation of medium to large machine tools (5 m³ – 50 m³) capable of reducing measurement times by 20 % without the need for stationary measurement locations and to allow in-process machine behaviour to be investigated.
  5. To facilitate the take up of technology & measurement infrastructure developed, by the measurement supply chain (NMIs & DIs), standards organisations (ISO) and end users (aerospace, automotive and energy industries). The tools developed in the project will be targeted at industrial applications and knowledge should be appropriately transferred to the relevant end users.