为斯图尔特平台设计实时安全控制，无需求解二次规划。
Design and Experimental Validation of Closed-Form CBF-Based Safe Control for Stewart Platform Under Multiple Constraints
- 直接给出满足多约束的安全控制闭式解，避免每步迭代求解。
- 实验表明计算时间降低超十倍，安全性能与传统方法相当。
- 适合对实时性要求高的并联机器人安全控制场景。
本文提出一种用于斯图尔特机器人平台的控制屏障函数（CBF）闭式解法，可同时处理多个位置和速度约束。该方法通过显式闭式控制律实现，无需在每个控制步骤中求解二次规划（QP），显著提升实时性。论文推导出闭式表达式非奇异的充要条件，确保多约束问题下CBF解的适定性。控制器在自建斯图尔特平台原型上进行了仿真与硬件实验验证，结果表明其在保障安全性的同时，计算时间减少一个数量级以上，性能接近基于QP的方法。实验视频可在项目网站获取。
原文摘要 · Abstract (English)
This letter presents a closed-form solution of Control Barrier Function (CBF) framework for enforcing safety constraints on a Stewart robotic platform. The proposed method simultaneously handles multiple position and velocity constraints through an explicit closed-form control law, eliminating the need to solve a Quadratic Program (QP) at every control step and enabling efficient real-time implementation. This letter derives necessary and sufficient conditions under which the closed-form expression remains non-singular, thereby ensuring well-posedness of the CBF solution to multi-constraint problem. The controller is validated in both simulation and hardware experiments on a custom-built Stewart platform prototype, demonstrating safetyguaranteed performance that is comparable to the QP-based formulation, while reducing computation time by more than an order of magnitude. The results confirm that the proposed approach provides a reliable and computationally lightweight framework for real-time safe control of parallel robotic systems. The experimental videos are available on the project website. (https://nail-uh.github.io/StewartPlatformSafeControl.github.io/)
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