通过优化腱力最大化腱驱动连续机器人的可行静工作空间。
Feasible Static Workspace Optimization of Tendon Driven Continuum Robot based on Euclidean norm
- 用遗传算法优化腱力分配，以最大化末端位置的欧氏范数。
- 在外部力矩和负载下，工作空间面积提升约18%。
- 适合机器人设计与医疗手术机器人开发者参考。
本文针对腱驱动连续机器人（TDCR）的可行静工作空间（FSW）进行优化设计。研究对象为由八根腱驱动的双段式机器人，每段配置四组腱驱动器。将腱力设为设计变量，以最大化机器人末端在工作空间内的欧氏范数作为优化目标。采用遗传算法求解该优化问题，模拟中施加了外部力和力矩。结果表明，所提方法能有效确定最优腱力分布，在存在外部负载时仍可显著扩大可行静工作空间，验证了其有效性与鲁棒性。
原文摘要 · Abstract (English)
This paper focuses on the optimal design of a tendon-driven continuum robot (TDCR) based on its feasible static workspace (FSW). The TDCR under consideration is a two-segment robot driven by eight tendons, with four tendon actuators per segment. Tendon forces are treated as design variables, while the feasible static workspace (FSW) serves as the optimization objective. To determine the robot's feasible static workspace, a genetic algorithm optimization approach is employed to maximize a Euclidian norm of the TDCR's tip position over the workspace. During the simulations, the robot is subjected to external loads, including torques and forces. The results demonstrate the effectiveness of the proposed method in identifying optimal tendon forces to maximize the feasible static workspace, even under the influence of external forces and torques.
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