OxTS LiDAR Inertial Odometry beta is here. Ensuring position accuracy in the absence of GNSS can be a challenge. Here at OxTS, our sensor fusion work continues to push the boundaries of what is possible without GNSS.
Our new technology accelerator team have been working on new sensor fusion projects that aim to prevent position accuracy degradation when GNSS signal is intermittent or completely blocked.
Owing to our calibration expertise, and experience combining highly accurate INS measurements and LiDAR data, we have developed a software solution that can use LiDAR data, alongside the navigation measurements from an OxTS INS, to mitigate the effects of localisation and georeferencing drift.
Furthermore, we’re delighted to announce that the OxTS LiDAR Inertial Odometry software is now available to test.
How does LiDAR Odometry get fused into the INS?
The new LiDAR Odometry feature will enhance navigation data in tough GNSS conditions. To do so, measurements from the LiDAR sensor must be fused into the INS. Using the OxTS GAD (Generic Aiding Data) interface the LiDAR data can be repurposed for use within the OxTS navigation engine.
Example Data – London Sky Garden
The following data was recorded during a recent test run to London. The location is the Sky Garden area within central London. This location was chosen because of the large amount of tall buildings and GNSS signal obstructions that would be encountered.
An OxTS Inertial Navigation System was mounted on a car alongside a Hesai LiDAR sensor. The OxTS LiDAR Inertial Odometry software was used to mitigate any localisation and georeferencing drift caused by GNSS signal dropout. A total of eight laps of the specified route was undertaken.
The below before and after KML trail screenshots illustrate the navigation data performance improvement with LiDAR Inertial Odometry enabled.
The KML trails above clearly show the difference that the OxTS LiDAR Inertial Odometry software has on navigation data reliability, consistency and predictability. In areas where GNSS signal was most difficult to obtain, such as skyscrapers, localisation drift was, as expected, most severe. With LiDAR Inertial Odometry enabled, localisation drift waskept to a minimum and the data output was much more consistent during all eight laps of the route.
Contact us using the form below for more information on this data set.
Test the new LiDAR Odometry feature yourself.
You can test the software yourself, or alternatively send us your data to process and we will highlight the expected performance improvement.
Complete the form here and one of our team will be in touch to provide you with the beta version of the software, or provide you with a secure link so you can send us your data to process.
Want to learn more?
Webinar
The increasing popularity of LiDAR for autonomy and survey perception applications has in turn enabled developers to increase performance of these sensors while improving affordability.
This performance improvement has seen LiDAR become a valuable localisation aiding source capable of enhancing navigation data quality in urban environments.
During this webinar OxTS Head of Product – New Technology, Paris Austin, is joined by OxTS Director of Core Markets, Simon Thompson, to discuss how sensor fusion using LiDAR can improve the quality of navigation data for groundtruthing and georeferencing applications – watch the recording
Industry Article
At OxTS our brand promise is “navigation experts”. Our commitment to our customers is that we will keep innovating until we can help them truly ‘navigate anywhere’ – with or without GNSS. We are taking our products forward in that direction by first enhancing urban navigation data quality.
We know that without accurate positioning and orientation in all environments many autonomy and surveying applications are impossible to execute to the required level of quality.
Whether it is an ADAS feature validation test on the open road, or a mobile mapping application, navigation data is at the heart of groundtruthing and georeferencing applications – continue reading