ByteWrist: A Parallel Robotic Wrist Enabling Flexible and Anthropomorphic Motion for Confined Spaces
Jiawen Tian, Jingchao Qiao, Liqun Huang, zhongren cui, Xiao Ma, Jiafeng Xu, Zeyu Ren
AI summary
Problem
Existing serial and parallel robotic wrists fail to simultaneously achieve the compactness, flexibility, and structural stiffness required for precise manipulation in narrow, confined spaces.
Approach
The authors developed a nested three-stage parallel drive mechanism integrated with arc-shaped end linkages and a central spherical joint, supported by complete forward/inverse kinematic and numerical Jacobian modeling.
Key results
- Nested three-stage linkage minimizes volume while enabling independent multi-DOF control
- Arc-shaped end linkages optimize force transmission and expand motion range
- Narrow-space grasping completed in ~50% less time than Kinova serial-wrist counterparts
- Successful dual-arm deformable object manipulation with 116 hours of automated data collection
Why it matters
Enables reliable robotic manipulation in constrained environments like medical cavities, home cabinets, and precision assembly lines where traditional wrists fail.
Abstract
This paper introduces ByteWrist, a novel highly- flexible and anthropomorphic parallel wrist for robotic manip- ulation. ByteWrist addresses the critical limitations of existing serial and parallel wrists in narrow-space operations through a compact three-stage parallel drive mechanism integrated with arc-shaped end linkages. The design achieves precise RPY (Roll- Pitch-Yaw) motion while maintaining exceptional compactness, making it particularly suitable for complex unstructured en- vironments such as home services, medical assistance, and precision assembly. The key innovations include: (1) a nested three-stage motor-driven linkages that minimize volume while enabling independent multi-DOF control, (2) arc-shaped end linkages that optimize force transmission and expand mo- tion range, and (3) a central supporting ball functioning as a spherical joint that enhances structural stiffness without compromising flexibility. Meanwhile, we present comprehensive kinematic modeling including forward / inverse kinematics and a numerical Jacobian solution for precise control. Empirically, we observe ByteWrist demonstrates strong performance in narrow-space maneuverability and dual-arm cooperative ma- nipulation tasks, outperforming Kinova-based systems. Results indicate significant improvements in compactness, efficiency, and stiffness compared to traditional designs, establishing ByteWrist as a promising solution for next-generation robotic manipulation in constrained environments.