MiniBEE: A New Form Factor for Compact Bimanual Dexterity
Islam, Sharfin, Chen, Zewen, He, Zhanpeng, Bhatt, Swapneel, Permuy, Andres, Taylor, Brock, Vickery, James, Lu, Zhengbin, Zhang, Cheng, Piacenza, Pedro, Ciocarlie, Matei
–arXiv.org Artificial Intelligence
Abstract-- 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. 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. T o 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. In recent years, bimanual robotic manipulators have shown remarkable dexterity. The combination of imitation learning from human demonstrations and two well-articulated kinematic chains has enabled such systems to use simple parallel grippers to autonomously perform highly dexterous tasks [1]-[7], with robustness to initial conditions or perturbations encountered during execution [8]-[10]. To achieve these results, current systems typically rely on the combination of two 6-or 7-degree-of-freedom (DOF) robotic arms.
arXiv.org Artificial Intelligence
Nov-12-2025
- Country:
- North America > United States (0.04)
- Genre:
- Research Report (0.66)
- Technology:
- Information Technology > Artificial Intelligence > Robots > Manipulation (0.66)