为降低十二杆张拉整体机器人（SC-12）在执行星球探测相关任务时的驱动及时间成本，提出了一种基于粒子群天牛须混合算法的索驱动优化策略。首先，基于SC-12的初始几何构型建立机器人等效模型，考虑重力矩及索调控量等多重约束，构建以驱动前后体系应变能差值为目标的驱动优化模型，克服了驱动过程中可能发生的索杆共面及基础底面异面的问题。通过非刚体运动分析方法确定不平衡状态下机器人的姿态，并利用粒子群天牛须混合算法获取最优驱动策略。最后，在机械系统动力学自动分析系统（ADAMS）中建立动力仿真模型，通过与杆驱动方式的对比验证了该方法在驱动成本优化方面的有效性。
To reduce the actuation and time costs associated with executing planetary exploration tasks by the twelve-bar tensegrity robot (SC-12), a cable driven optimization strategy based on the Particle Swarm Optimization-Beetle Antennae Search (PSO-BAS) hybrid algorithm is proposed. Firstly, an equivalent model of the SC-12 robot is established based on its initial geometric configuration. By considering multiple constraints such as gravity moment and cable regulation, a drive opti-mization model is constructed with the objective of minimizing the difference in strain energy of the system before and after actuation. This approach overcomes potential issues such as coplanar cable-rod configurations and non-coplanar base planes that may arise during the actuation process. By Non-Rigid-body Motion Analysis (NRMA), the posture of the robot in an unbalanced state is determined. Furthermore, the optimal actuation strategy is obtained using the PSO-BAS hybrid algorithm. Finally, a dynamic simulation model was established in the Automatic Dynamic Analysis of Mechanical Systems (ADAMS). By comparing it with the rod-driven method, the effectiveness of this approach in optimizing driving costs was verified.
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