AGRICULTURE DIVISION
Data drives the development of autonomous vehicles. During autonomous operation, an R&D vehicle gathers data from the sensors and produces logs. The raw sensor data, as well as onboard logs, is then used by engineers to improve onboard autonomy systems, including machine learning.
Onboard data is typically transferred to a large-scale storage device by fiber optics or by removable or swappable drives. Once the data is processed by engineers, it’s retained and used later for regression testing and engineering.
Sensor Integration, Sensor Calibration, Sensor Logging, Image Capture, Vehicle Storage
Manage data lifecycle, Raw sensor data, Tagging/annotation, Sensor truth, Data archiving, HD map creation
Sub-System development, Machine learning training, Watchdog Application, Security, Compliance
SIL/HIL full simulation, Static world creation, Vehicle integration, Generate synthetic data, Machine learning
Data intelligence is an important part of autonomous vehicle research and development. Accelerate your R&D programs with high-performing, economical data-storage solutions, sensor truth benchmarking, simulation, data tagging and annotation, data-mining tools, mapping and more. Before you choose a solution, consider your requirements.
With 10 years of in-house experience in autonomy and advanced driver assistance systems (ADAS), combined with support from our expert partners, we can help you get up and running quickly. AutonomouStuff data intelligence solutions address common scenarios for ingesting, storing and archiving vast amounts of data from onboard sensors and systems.
Calculate data used per hour from sensors provided by AutonomouStuff, to get a better idea on storage needs.
Learn about real-life, cost-effective solutions that support massive datasets with shared, long-term storage.
Selecting simulation software can feel overwhelming, but the team at AutonomouStuff wants to make the process as painless — and productive — as possible.
Discover where our data intelligence solutions are headed in the future.
Autonomous R&D vehicles are fitted with a variety of sensors, which are used by onboard autonomy systems and machine learning algorithms. The raw data from these sensors is used to improve and train the onboard machine learning algorithms. Cameras and LiDAR generate most of the data.