Uncertainty-Aware Shared Control for Vision-Based Micromanipulation

This paper presents an uncertainty-aware shared control and calibration method for micromanipulation using a digital microscope and a tool-mounted, multi-joint robotic arm, integrating real-time human intervention with a visual-motor policy. Our calibration algorithm leverages co-manipulation control to calibrate the hand-eye transformation without re-quiring knowledge of the kinematics of the microtool mounted on the robot while remaining robust to camera intrinsics errors.<br/>Experimental results show that the proposed calibration method achieves a 39.6% improvement in accuracy over established methods. Additionally, our control structure and calibration method reduces the time required to reach single-point targets<br/>from 5.74 s (best conventional method) to 1.91 s, and decreases trajectory tracking errors from 392 µm to 40 µm. These findings establish our method as a robust solution for improving reliability in high-precision biomedical micromanipulation.