Bridge Labs

Problem

Training robotics perception models requires large volumes of realistic, physics-accurate environments, which are expensive to build by hand.

What I built

A generative LIDAR and physics-aware AI pipeline that builds reality-based environments for synthetic robotics training data, using NVIDIA Isaac Sim and World Labs.

System & workflow

A generation pipeline that pairs World Labs environment generation with Isaac Sim's physics and LIDAR simulation to output reality-based synthetic training environments.

My contribution

Built the pipeline connecting environment generation to physics-based simulation for training-data output.

Challenges & decisions

Making generated environments physically consistent enough that LIDAR output is usable as real training data, not just visually plausible.

Results

In active development; no public build yet.