AI & Machine Learning

LiDAR Data Labeling for Autonomous Systems

Delivered precise LiDAR data labeling to support autonomous system development, enabling machine learning models to accurately interpret complex 3D point cloud data.

GeoMap

San Francisco, USA 🇺🇸

Mar 2026

AI & Machine Learning

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Project Details

Client: GeoMap
Location: San Francisco, USA 🇺🇸
Date: March 2026
Category: AI & Machine Learning

Tools & Technologies

Supervisely Scale AI LiDAR processing platforms

LiDAR Data Labeling for Autonomous Systems

AI & Machine Learning

The Challenge

The client required high precision labeling of dense and complex 3D LiDAR point clouds. Consistency across annotators and scalability for large datasets were major challenges impacting model accuracy.

The Solution

Led end to end LiDAR annotation workflows including object classification, segmentation, and labeling

Developed annotation guidelines and standards to ensure high precision

Trained and managed remote teams to maintain accuracy and efficiency

Implemented quality control systems to verify consistency across annotators

The Outcome

Improved autonomous system model accuracy through high quality labeled datasets
Delivered scalable labeling solutions for large, complex LiDAR datasets
Strengthened data consistency across multiple annotators, reducing errors and improving reliability
Enhanced workflow efficiency and team performance for long term annotation projects