Ropedia launches next-gen wearable for robotic AI training data

The device is designed to capture egocentric video with a 360-degree field of view, using four camera streams, spatial audio and motion data to record human activity as the wearer perceives it. It aims to provide the high-quality, varied data needed to train robotic AI foundation models, especially for humanoid and arm-based applications.

“Scaling laws make large language models work because more data equals better results,” said co-founder and Chief Executive Zhaoxi Chen. “Physical AI runs on the same law, except the data needs to come from someone actually doing the job. For example, imagine learning how to drive by only sitting in the back seat.”

The company said HOMIE Gen2 treats human experience as immersive, location-specific training that AI models can translate into virtual training, which can then be used to mimic physical actions. A single session can train for several target tasks or reconstruct a single episode of human behavior.

“Hardware-synchronizing four camera streams, spatial audio and inertial data to within 50 microseconds means our models can treat a session as one continuous signal instead of reconciling four separate ones,” said Chief Scientist Ziwei Liu, an associate professor at Nanyang Technological University.

The wearable requires no external rig, allowing users to capture data in homes, factories or shopping malls without elaborate setup. Deployment is 10 times faster than the previous generation and costs about one-12th the cost of a full lab capture.

Ropedia did not disclose pricing but said business users can purchase the devices individually or in bundles. The company is open to partnerships, pilot programs and direct sales. The launch follows a $22 million pre-Series A funding round raised last month.