Tokyo-based Enactic_ai fully open-sources OpenArm, a 7-DOF humanoid robotic arm including 3D-printable CAD files, BOM, motor firmware, ROS2 drivers, web-based MuJoCo simulation, Isaac Sim integration, and a leader arm for zero-latency force-feedback teleoperation, dramatically lowering the cost barrier for embodied AI research.
The article demystifies eight common terms in embodied intelligence data collection—Ego, Exo, GoPro, UMI, Teleoperation, MoCap, Data Glove, and Robot Trajectory—explaining their meanings, how they differ, and why each is crucial for building effective robot learning datasets.
HumDex combines wireless inertial motion capture, a learning‑based hand‑redirection network, and a two‑stage pre‑training/fine‑tuning pipeline to deliver portable, high‑precision teleoperation for humanoid robots, cutting data‑collection time by 26% and raising remote‑operation success to 91.7% while enabling zero‑shot generalization across unseen objects and scenes.
This article walks you through the entire process of assembling a low‑cost Lerobot SO‑ARM100 6‑DOF robotic arm, configuring its Feetech servos, calibrating motion, adding dual cameras for teleoperation, collecting a dataset, and training a reinforcement‑learning policy locally or on cloud GPUs, with detailed troubleshooting tips and code examples.
