More Precise and Faster: Dual-Scale Teleoperation for Manipulator in Large Workspace

In practical robotic applications, most tasks require a combination of large-range motion and fine operation. Effectively coordinating these two aspects poses a significant challenge due to the mismatch between the limited workspace of the leader robot and the expansive workspace of the follower manipulator. To address this issue, we propose a dual-scale teleoperation framework that enables the seamless integration of large-range movement and fine operation. Furthermore, we design an adaptive force feedback strategy based on fuzzy logic, which dynamically allocates environmental contact and constraint forces between the dual leaders with different mapping scales, ensuring closed-loop control of the system. A comprehensive analysis of the framework's stability and transparency is provided. Finally, the proposed force feedback teleoperation framework is experimentally validated against existing methods. In the fixed-point alignment task, the proposed method achieves a success rate of 85.7% and reduces completion time by approximately 10%. In the narrow passage navigation task, the manipulator successfully passes through a 120 mm-wide channel (with a manipulator width of 115 mm), while significantly reducing the number of collisions. These experimental results demonstrate the effectiveness of the proposed approach in achieving fine operations within large workspaces.