MiniBEE: A New Form Factor for Compact Bimanual Dexterity
This addresses the issue of system complexity and limited workspace for researchers and practitioners in robotics, offering a novel design but with incremental improvements in dexterity.
The paper tackled the problem of bimanual robot manipulators being complex and underutilizing workspace by introducing the MiniBEE, a compact system with reduced-mobility arms that achieved full relative positioning between grippers, enabling wearable data collection and deployment on standard arms for robust bimanual manipulation.
Bimanual robot manipulators can achieve impressive dexterity, but typically rely on two full six- or seven- degree-of-freedom arms so that paired grippers can coordinate effectively. This traditional framework increases system complexity while only exploiting a fraction of the overall workspace for dexterous interaction. We introduce the MiniBEE (Miniature Bimanual End-effector), a compact system in which two reduced-mobility arms (3+ DOF each) are coupled into a kinematic chain that preserves full relative positioning between grippers. To guide our design, we formulate a kinematic dexterity metric that enlarges the dexterous workspace while keeping the mechanism lightweight and wearable. The resulting system supports two complementary modes: (i) wearable kinesthetic data collection with self-tracked gripper poses, and (ii) deployment on a standard robot arm, extending dexterity across its entire workspace. We present kinematic analysis and design optimization methods for maximizing dexterous range, and demonstrate an end-to-end pipeline in which wearable demonstrations train imitation learning policies that perform robust, real-world bimanual manipulation.