Real World Robotics

This project developed a low-cost, anthropomorphic robotic hand system specifically engineered for efficient data collection using data gloves for imitation learning on manipulation tasks. The 16 DOF (Degrees of Freedom) tendon-driven robotic hand features integrated force sensors in each fingertip and a sophisticated control system that enables precise teleoperation through human hand motion capture.

The system addresses key challenges in imitation learning research: the high cost of dexterous robotic hands and the difficulty of collecting high-quality expert demonstration data. By combining innovative mechanical design, advanced control algorithms including retargeting and Gaussian Process modeling, and streamlined data collection workflows, the project enables researchers to focus on developing capable control policies rather than struggling with hardware limitations and data quality issues.