Our goal is to remove the barrier between traditional ways of aerial mobility and the innovative AI-based opportunities. We are convinced, that a deeper understanding of the progressive potential for self-flying vehicles will change our behaviors of movement, transportation and aerial reconnaissance in the same fundamental way the invention of the airplane did decades before.
We develop the brain of future mobility towards Level 5 Autonomy.
We deliver full-stack aerial AI software including Sensor-Fusion, Perception, Scene-Understanding, SLAM such as Planning and Control.
Our brains look with the eyes of 360 cameras, 3D Lidar and 3D Radar. The data is fused in a 3D environmental model accompanied with accurate positioning systems.
We record and deliver large scaled multi-sensoral data-sets with Ground Truth (e.g. 3D Semantics) to train your specific AI.
We develop the AI platform for Autonomous Unmanned Aerial Vehicles (UAV), Autonomous Air-Taxis such as Autonomous Vertical Take Off and Landing (VTOL) vehicles.
Our HD-SLAM algorithm measures every environment in 3D based on the latest Lidar technology. This method is highly accurate and effective such as cost-conscious.
Our AI parses every scene automatically to detect any kind of object (trees, agricultural fields, bridges, building, rails) for any kind of task.
See a full 360 perception flight demo. Toggle between 360 camera (3D), Sensor Fusion (Camera + Lidar) and AI based Semantic Segmentation Views. What does the Self-Flying vehicle see?
Our AI based Lidar SLAM semantically reasons every 3D point around the flying vehicle. This leads to a complete interpretable 3D map for full autonomy. A 3D interpretation leads to full process automation like automatic infrastructure analysys (buildings, streets, rails) or agriculture use cases (tree counting).
We're not just talking about AI, we're doing AI. See our latest accepted papers:
AI-Survey for Self-Flying Vehicles: Exploring the Challenges of Deep Learning
Aerial LiDAR reconstruction using conditional GANs
Aerial GANeration: Towards Realistic Data Augmentation Using Conditional GANs
Real-time Dynamic Object Detection using Prior 3D-Maps
Spleenlab was founded by a team of engineers, researchers and entrepreneurs. As early pioneers of autonomous flying software engineering we are excited about the possibilities the AI based air mobility will bring. With our experience and our skills in deep learning, autonomous mobility, vision and graphics we are working day after day to make this groundbreaking future a reality.
Dr. Stefan Milz
Head of R & D
Dipl. Hdl. Tobias Rüdiger
Head of Operations & Finance
Sebastian Süß, M.A.
Head of Marketing & Sales
Florian Ölsner, B.Eng.
Machine Learning Scientist
Friedrich Moeller, M.Sc.
Software Engineer, PhD candidate
Laser and Sensor Engineering
Visual Design Lead
Machine Learning Engineer
Chris Hagen, Dipl. Ing.
Dr. Patrick Wohlfahrt
Machine Learning Advisor
Researcher at Harvard University
spleenlab UG (haftungsbeschränkt)
Amtsgericht Jena HRB 511858
Geschäftsführer Stefan Milz, Tobias Rüdiger, Sebastian Süß