With the growing developments in automotive technology, the need for accurate, reliable and robust ground reference has emerged. Global Navigation Satellite System (GNSS)+Inertial Navigation System (INS) post-processing is an essential component of achieving high-accuracy ground truth, especially when addressing autonomy in the most challenging environments.
Testing autonomous vehicles usually starts in a confined area, with open sky conditions and minimal multipath interference. However, this type of environment cannot reflect the real-world conditions when GNSS signals are blocked by trees, buildings, overpasses or other obstructions.
The questions that results are: How do you know if your autonomous system works well in the real world and what can you use to determine truth for the track that your vehicle drove?
The University of Waterloo, a leading authority on autonomous aerial and ground vehicles, uses GNSS+INS post-processing to assist in collecting thousands of kilometers of data in good, bad and ugly weather conditions.
Steven Waslander
They use the data to create a driving dataset for a new road that focuses on all-weather autonomy challenges, from 3D object detection and tracking, precise localization and mapping to semantic segmentation of the driving environment using omnidirectional vision and light detection and ranging (LiDAR) data.
“High-accuracy ground truth on vehicle motion is essential for the assessment of localization and mapping results, and greatly improves the rate at which precise labels can be generated for vehicle tracks through the environment,” said Steven Waslander, associate professor, mechanical and mechatronics engineering at the University of Waterloo.
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GNSS+INS use cases
GNSS+INS post-processing software is an effective tool for autonomous vehicles in creating dataset benchmarks, comparing real-time and post-processed GNSS quality and more. Whether users are attempting to evaluate potential sensor suites, benchmark their own solutions or generate high-definition (HD) maps, centimeter-level reference solutions are becoming a growing necessity.
Photo: NovAtel
Combining GNSS with INS extends the capability of traditional GNSS products by providing a full 3D attitude solution (roll, pitch, heading) and by providing a solution even during temporary outages in GNSS reception.
Real-time GNSS+INS system accuracy is also limited by the quality of the inertial measurement unit (IMU) and the duration of GNSS outage periods. The performance of these systems is greatly improved through GNSS+INS post-processing.
GNSS+INS post-processing maximizes the accuracy of the solution by processing previously stored GNSS and IMU data forward and reverse in time, and combining the results. The position, velocity and attitude solution can be smoothed and output at the required data rate, desired sensor location and coordinate frame.
Using a GNSS+INS post-processing software allows users to establish an ultra-precise ground-truth reference for testing. Users can evaluate different sensor suites, evaluate iterative software development and compare analytics tools for evaluating test environments.
Post-processing can also provide flexible data manipulation by producing customized data formats for exporting information, comparing real-time and post-processed quality, and revisiting tests through exports to Google Earth.
Autonomous leaders count on NovAtel as the standard for truth in many developments and autonomous kits.
Inertial Explorer: A GNSS+INS post-processing solution
Logo: NovAtel
NovAtel’s Waypoint® Software, Inertial Explorer®, is a powerful GNSS+INS post-processing suite. Positioning algorithms allow users to compare and assess the reliability and accuracy of their real-time solution. Inertial Explorer can take NovAtel real-time GNSS data and correct the solution using various base-station measurements, taking a meter-level solution and improving it to centimeter-level, regardless of the corrections done in real-time. Inertial Explorer removes up to 95 percent of position error over GNSS outages as compared with a real-time solution.
Click to enlarge. Images: NovAtel.
AutonomouStuff, the sole vehicle supplier of the Baidu Autonomous Driving ecosystem Apollo project, uses post-processing to verify proper installation and to create a baseline dataset to benchmark against the data collected on autonomous vehicles in real-time.
Terry Lamprecht
“Inertial Explorer is a valuable tool that allows AutonomouStuff to provide a better service to our customers. It also provides our team with a very accurate source of positioning data that can be used internally for future development,” said Terry Lamprecht, director of products at AutonomouStuff.
NovAtel’s Waypoint Inertial Explorer is the perfect complement to NovAtel’s SPAN® real-time GNSS+INS deeply coupled navigation systems.
Inertial Explorer Key Features:
- Import GNSS data from multiple receiver manufacturers
- Download utility provides access to thousands of publicly available base stations
- DMI (wheel sensor) data input to further maximize performance in challenging environments
- Customizable export tool permits reproduction of most ASCII file formats
- Optionally solve the IMU to GNSS lever arm
- Preloaded error models for most popular IMUs as well as customer-created IMU error models
- Streamlined Project Wizard for quick startup
To learn more about NovAtel and Waypoint Inertial Explorer, visit www.novatel.com. Interested in seeing how Waypoint Inertial Explorer works firsthand? Register below to begin your 7-day free trial.
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This page was produced by North Coast Media’s content marketing staff in collaboration with NovAtel. NCM Content Marketing connects marketers to audiences and delivers industry trends, business tips and product information. The GPS World editorial staff did not create this content.
Header video provided by NovAtel.
