Phone2Act: A Low-Cost, Hardware-Agnostic Teleoperation System for Scalable VLA Data Collection
This work addresses the high cost and hardware dependency of existing vision-language-action (VLA) models, which rely on expensive, platform-specific demonstration data that lacks cross-platform reusability. The authors propose a low-cost, hardware-agnostic teleoperation system leveraging a smartphone and Google ARCore to achieve six-degree-of-freedom control. Built on a modular ROS 2 architecture, the system decouples control logic from hardware through pluggable bridge nodes, enabling seamless integration across diverse robotic platforms. It synchronizes multi-camera RGB video with robot state data to directly generate datasets in LeRobot format. Without requiring code modifications, the framework supports end-to-end workflows—from data collection to VLA model fine-tuning—spanning industrial collaborative robots to low-cost dual-arm setups. Fine-tuning the GR00T-N1.5 model on 130 task demonstrations achieves a 90% success rate on multi-stage pick-and-place tasks executed on a real Dobot CR5 robot.