OxTS manufacture cutting edge GNSS-aided Inertial Navigation Systems (INS). OxTS INS devices are used across the world in a multitude of applications where accurate and reliable localisation and groundtruth data is required.
Any navigation engine that uses GNSS to calculate position is susceptible to position drift and the longer the device is without GNSS signal, the more severe the drift becomes.
Position drift isn’t a challenge in open-sky conditions, however, in areas with poor GNSS visibility, such as urban canyons, ensuring position drift is kept to a minimum is critically important. To minimise the effects of position drift, other aiding sources, such as LiDAR, are required.
OxTS LIO, is an optional feature of OxTS INS devices that uses LiDAR sensor data to improve vehicle trajectory measurements. The enhanced measurements are then used to constrict position drift in the absence of GNSS.
LIO Technical Paper
Download the OxTS LIO technical paper and learn more about how the new feature works alongside OxTS INS devices.
The technical paper covers several key topics including…
- How LIO works
- Performance evaluations – Oxford and London
- Potential applications and use cases
- What is required to get the most out of LIO
How does LIO work?
LiDAR Inertial Odometry (LIO) uses LiDAR as an aiding source to the INS.
Using LiDAR data alongside the navigation data from an OxTS INS mitigates the effects of position drift in sub-optimal GNSS conditions.
The feature combines the data from any LiDAR sensor natively available in OxTS Georeferencer, with the navigation output from an OxTS INS using the OxTS Generic Aiding Data (GAD) engine in post-processing.
The outcome is improved position accuracy in the absence of the ideal number of GNSS satellites for RTK accuracy.
Where can I use LIO?
In areas with good satellite visibility LIO will offer minimum benefit. As the optimum number of satellites will be in view, using an additional aiding source to achieve RTK accuracy should not be needed.
Where customers will witness most performance improvement is in environments where GNSS signal is difficult to obtain consistently, such as urban canyons.
A LiDAR sensor builds up a picture (digital replica or pointcloud) of its environment by emitting beams of light and measuring the time taken to return. Understanding the time it takes for the light to return, enables the sensor to calculate the distance to an object.
Therefore, built up areas, such as urban canyons, with flat planes, are perfect environments to get the most performance improvement from LIO.
Test data – Central London, UK
During the LIO development phase, the feature was tested in an environment where end users will get most value – an urban canyon. The tall skyscrapers prevalent in London, present a significant challenge for IMU/GNSS based systems. Constant GNSS interruption and multi-path errors mean that it is very difficult to obtain consistently accurate position data.
The white KML trail shows the vehicle under test’s position without enabling the LIO feature. The red KML trail is with LIO on.
Compatible LiDAR sensor families
The LIO feature code is compatible with many automotive grade LiDAR sensor families.
Trial the beta version of LIO today and witness the performance improvement yourself!
Users of OxTS Inertial Navigation Systems can trial the beta version of LIO for free today!
Complete the form and one of our developers will be in touch to provide you with the software!
Alternatively, send us your data to firstname.lastname@example.org and we will process it for you!