You have a well-functioning autonomy system but have challenges with reliability in edge-cases? Integrate a driveblocks perception module as a parallel pipeline to your in-house solution, e.g., using LIDAR or RADAR sensors and combine the results with a sensor fusion module.
Your sensor generates unprecedented level of detail when scanning the environment and vehicle networks struggle to cope with the generated data amount? Integrate a set of driveblocks perception modules to preprocess the data and enable customers to use object list, drivable space and flow-based odometry interfaces.
Your fleet consists of multiple different vehicles with varying geometries and tasks? The Mapless Autonomy Platform allows you to leverage a pre-configured perception and sensor-fusion solution with continuous safety, security, and feature updates. The open-architecture design lets you customize modules while relying on a solid and safe foundation.
Technology start-up driveblocks, a software specialist for fully autonomous driving of commercial vehicles, has closed a 2.2 million euro seed round led by Rethink Ventures and Bayern Kapital. Angel investor Joachim Drees (former CEO of MAN SE and MAN Truck & Bus SE) and existing investor Friedrich & Wagner Holding also provided fresh capital. The founding team intends to use the funds primarily for the further development of driveblocks’ core technology: the Mapless Autonomy Platform.
driveblocks releases a new revision of its core product, the Mapless Autonomy Platform. The release improves its ability to operate in industrial vehicle settings such as construction and agriculture. In addition, the new software release supports customers in understanding the performance for their respective use-case in detail and identify improvement potentials.
driveblocks, a technology company providing perception software for mapless autonomous driving, rolls out an updated version of its core product, the Mapless Autonomy Platform with major improvements with respect to embedded deployments.
Transformer neural networks leverage context information via attention-mechanisms. Learn more about how we leverage this to improve edge-case performance in the Mapless Autonomy Platform.