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 to create HD maps of an entire city, navigation data is at the heart of groundtruthing and georeferencing applications. Without it our customers would be unable to produce data with centimetre-level absolute accuracy in the global frame, preventing them from going to market with an ADAS feature or selling map data to their own customers.
With our innovation work in 2023 and onwards we plan to offer improved navigation performance on the open road and in dense urban environments, where customers do not get perfect GNSS but require similar levels of accuracy to what we deliver on an automotive proving ground.
Through this work we will bring our customers closer to the goal of OxTS which is to help them “navigate anywhere” as well as extending our capability to more customers in new applications.
The approach?
Sensor fusion is at the heart of all of our navigation work. Originally the fusing of GNSS and IMU data gave OxTS the traditional INS product that has served our customers for two decades. The addition of a wheel speed sensor in current applications enables further enhancement to navigation performance but more sensors than ever before are available and have the potential to aid the navigation solution we are offering.
Using sensors with mutually exclusive sensing approaches means that error growth manifests in a way that allows for logical and reliable validation. If four sensors agree and one contradicts with them it is an easy decision to reject the outlier. This is often better than using five of the same sensor where the error characteristics are common and so if one suffers a drop in performance based on an event, they all could.
The solution?
The first step is to pick a sensor with mutually exclusive characteristics to GNSS and IMUs. LiDARs growth in popularity for autonomy and survey applications means that LiDAR sensors are a prime candidate as an aiding sensor due to their increasing performance levels and decreasing cost. The 3D nature of operation means that LiDAR can be used to identify features in the environment over time and calculate a velocity vector and constrain IMU drift in all axes of velocity through odometry updates. This allows for enhanced dead reckoning in GNSS denied environments. Pair this with the advanced GNSS processing of OxTS’ gx/ix algorithm and in house IMU design and the navigation solution becomes much more robust in a GNSS restricted environment.
If you’re interested in learning more about using sensor fusion to ensure position accuracy in all environments, send us a message to info@oxts.com for a confidential conversation about your project.
Webinar: Using LiDAR to enhance urban navigation data quality
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 all the time.
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, was 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.
By watching the webinar you will learn more about:
- What sensor fusion is, and how can it help you ensure accurate position in all environments
- Which sensors can be utilised in a sensor fusion framework
- Example sensor fusion results
The webinar is free to attend and a copy of the recording will be sent to everybody who registers after the event.
