LeHome Challenge (ICRA 2026): Bimanual Cloth Folding via Imitation Learning

Overview

The leHome Challenge (ICRA 2026) is a Deformable BiManipulation Challenge focused on folding laundry using a bimanual SO-101 robot. Teams must train policies capable of manipulating deformable objects — one of the hardest open problems in robot learning due to the near-infinite configuration space of cloth.

We finished 54th out of 230+ teams.

Data Collection

Automatic data collection was attempted by extracting privileged information about the cloth mesh directly from the Isaac Sim scene and passing goal poses to cuRobo for bimanual IK solving and motion planning. In practice this pipeline was too brittle — cuRobo IK failures and sim–real cloth geometry mismatches meant trajectories rarely transferred to usable demonstrations.

We fell back to manual teleoperation on the physical SO-101 arms, then significantly expanded the dataset through data augmentation: applying colour-jitter, brightness, contrast, and blur filters to camera observations to improve policy generalisation across lighting conditions.

Policy

Five policy architectures were trained and evaluated:

SmolVLA achieved the highest task success rate across our evaluations. All policies were trained using the LeRobot framework with PyTorch.

Results

Ranked 54th / 230+ teams at the leHome Challenge (ICRA 2026).