MiniBEE: A New Form Factor for Compact Bimanual Dexterity
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , , , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866917361322295296 |
|---|---|
| author | Islam, Sharfin Chen, Zewen He, Zhanpeng Bhatt, Swapneel Permuy, Andres Taylor, Brock Vickery, James Lu, Zhengbin Zhang, Cheng Piacenza, Pedro Ciocarlie, Matei |
| author_facet | Islam, Sharfin Chen, Zewen He, Zhanpeng Bhatt, Swapneel Permuy, Andres Taylor, Brock Vickery, James Lu, Zhengbin Zhang, Cheng Piacenza, Pedro Ciocarlie, Matei |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_01603 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | 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 Robotics 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. |
| title | MiniBEE: A New Form Factor for Compact Bimanual Dexterity |
| topic | Robotics |
| url | https://arxiv.org/abs/2510.01603 |