• Developing a bimanual robotic manipulation system in the UW Robotics and State Estimation Lab, focusing on robust real-world teleoperation and data-driven learning.
• Collaborated closely with PhD researcher to improve teleoperation smoothness, reducing control discontinuities and increasing task stability during manipulation.
• Designed and executed targeted data collection pipelines to diversify the training dataset for bimanual valve manipulation tasks.
• Identified and validated the importance of starting end-effector positions below the valve, enabling the learning algorithm to better avoid collisions and significantly improve generalization across manipulation scenarios.
• Contributed insights bridging robot control, data collection strategy, and learning performance, strengthening system robustnes