I will 3d lidar, point cloud annotation for vla, robotics, autonomous driving

I create accurate 3D training annotations for LiDAR and point-cloud datasets used in autonomous driving, robotics, mapping, and computer vision projects.

I turn raw LiDAR/point-cloud data into clean, consistent, training-ready annotationsfollowing YOUR classes, rules, and output format.

What I handle:

• Oriented 3D cuboids / bounding boxes
• Object classification
• Persistent tracking IDs across frames
• Semantic and instance segmentation
• Occlusion labels
• Full QA and consistency checks

I work with common formats and can export in the structure your pipeline needs. Complex scenes, heavy occlusion, and multi-frame sequences are normal for me.

Perfect for:

VLA datasets, autonomous vehicles, robotics, computer vision, 3D detection/tracking, mapping, and spatial AI.

You send the data + guidelines. I handle the annotation + QA. You get organized data ready for training.

Zero-risk start: Get a completely FREE small pilot batch first and verify my accuracy, consistency, and quality before committing to the full project.

Complex dataset? No problem. Send a sample, class list, and requirements before ordering. Ill review the scope and confirm the best approach.