Sensor fusion labelling for robots, drones and vehicles
Labels for physical AI systems that see the world through several sensors at once. For Autonomous systems, AgTech, robotics and drone startups.
The problem
A robot or drone sees the same scene through LiDAR and several cameras. When the labels disagree between sensors, the model learns two versions of one scene.
Work we take on
| Task | What you receive |
|---|---|
| 3D LiDAR segmentation | Point-level classes for each sweep, using your class list. |
| Multi-view camera tracking | Object identities kept consistent across cameras and frames. |
| Sensor-synchronised labelling | One set of labels aligned across LiDAR, cameras and other sensors by timestamp. |
How a batch moves
- Pre-label
- Segment Anything produces first-pass masks on camera frames. Live
- Who reviews it
- Annotators trained on 3D tools, with engineers checking edge cases. We are recruiting them now. Next
- Agreement check
- Blind multi-review on ambiguous items, tracked with Fleiss’ kappa and Cohen’s kappa. Next
- Status
- Taking pilot requests. Pre-labelling and security controls run today. Expert review starts with the first pilots.
Request a pilot for sensor fusion
Pilots start once our first expert reviewers are in place. Send a request now and we will reply by email.