OpenPyRo-A1: An Open Python-Based Low-Cost Bimanual Robot for Embodied AI

Abstract

Many real-world tasks, such as assembly, cooking, and object handovers, require bi-manual coordination. Learning such skills via imitation remains challenging due to dataset scarcity, mainly caused by the high cost of bi-manual robotic platforms and barriers to entry in robotics software. To address these challenges, we introduce (1) ROBOTNAME, a low-cost, bi-manual humanoid robot priced at approximately 14K. ROBOTNAME achieves 0.2 mm repeatability and supports a 5 kg payload per arm, and (2) a Python-first distributed control framework for seamless teleoperation, data collection, and policy deployment, designed for ease of use; moreover, the code-base is installable via pip. We conducted imitation learning experiments in both simulation and the real world, integrating the robot with perception models, motion planning, and a large language model. The results demonstrate that ROBOTNAME is a stable, user-friendly, and high-precision dual-arm platform. We expect that the ROBOTNAME hardware, control system, and curated dataset of bi-manual manipulation episodes will advance affordable and scalable dual-arm robotics