1. GNSS/INS – RT3000 v4
2. LiDAR – Hesai XT32
3. Software: NAVsuite, OXTS LIO

Environment: In this example OXTS LIO was tested inside a multi-storey car park. Upon entering the car park the RT3000 v4 GNSS/INS naturally did not have any access to GNSS updates. To overcome this, velocity updates from a Hesai XT32 LiDAR sensor were used to aid the navigation engine.

The outcome is more accurate data as can be seen when comparing the before and after point cloud screenshots above.

1. GNSS/INS – RT3000 v4
2. LiDAR – Hesai XT32
3. Software: NAVsuite, OXTS LIO

Environment: In this example OXTS LIO was tested in one of the most difficult areas for a GNSS/INS to operate, the ‘Sky Garden Quarter’ urban canyon in London, UK. During the data collection, there were regular GNSS signal interruptions and severe multi-path disruptions. In this case, OXTS LIO was used to improve position drift making the data both accurate and repeatable throughout each lap of the data collection.

1. GNSS/INS – RT3000 v4
2. LiDAR – Hesai XT32
3. Software: NAVsuite, OXTS LIO

Environment: Even a short tunnel can present a major test for a GNSS/INS. The longer a GNSS/INS is without GNSS signal updates, the more pronounced position drift becomes. In this example, OXTS LIO was used to keep the navigation solution on track throughout its journey through the tunnel. Not only did this lead to improved navigation data but also a clearer pointcloud, as can be seen by viewing the pillars in the example below.

1. GNSS/INS – RT3000 v4
2. LiDAR – Hesai XT32
3. Software: NAVsuite, OXTS LIO

Environment: As mentioned previously, because GNSS signal updates are blocked in a multi-storey car park, a GNSS/INS device must use an additional aiding source to navigate accurately. In this example OXTS LIO has been used to improve the navigation output. This has led to a more consistent data set.

1. GNSS/INS – RT3000 v4
2. LiDAR – Hesai XT32
3. Software: NAVsuite, OXTS LIO