新型并联机械腕让机器人在狭小空间更灵活精准地操作。
ByteWrist: A Parallel Robotic Wrist Enabling Flexible and Anthropomorphic Motion for Confined Spaces
- 三阶段并联驱动+弧形末端连杆,体积小且可独立控制多自由度。
- 实测在狭窄空间中运动能力优于柯尼卡瓦系统,刚度与效率显著提升。
- 适合家庭服务、医疗辅助等复杂非结构化场景的高精度操作。
本文提出ByteWrist,一种新型高灵活性、类人化的并联机械腕,用于机器人操作。该设计通过集成弧形末端连杆的紧凑三阶段并联驱动机构,克服了传统串行与并联腕在狭小空间作业中的局限。其能实现精确的RPY(滚转-俯仰-偏航)运动,同时保持极佳紧凑性,特别适用于家庭服务、医疗协助和精密装配等复杂非结构化环境。核心创新包括:(1) 嵌套式三阶段电机驱动连杆,减小体积并支持独立多自由度控制;(2) 弧形末端连杆优化力传递并拓展运动范围;(3) 中心支撑球作为球关节,增强结构刚度而不牺牲灵活性。此外,本文建立了完整的运动学模型,包含正/逆解及数值雅可比求解,实现精准控制。实验表明,ByteWrist在狭小空间机动性和双臂协同操作任务中表现优异,性能超越基于Kinova的系统,相较传统设计在紧凑性、效率和刚度方面均有显著提升,为受限环境下的下一代机器人操作提供了有力解决方案。
原文摘要 · Abstract (English)
This paper introduces ByteWrist, a novel highly-flexible and anthropomorphic parallel wrist for robotic manipulation. 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 environments 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 motion 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 manipulation 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.
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