关键词: 张拉整体机器人, 优化策略, 驱动成本, 星球探测, 粒子群天牛须混合算法

Abstract:

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. Considering multiple constraints such as gravity moment and cable regulation， a drive optimization 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. Using 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， dynamic simulations were performed using the mechanical system dynamics automatic analysis system （ADAMS） to compare the drive and time costs of different drive modes for robots with the same configuration. Additionally， the forward speed and energy cost of robots with different configurations （SC-12 and six-bar tensegrity robot） under the same drive mode were analyzed. The results confirm the superior motion performance of SC-12 in exploration tasks and validate the effectiveness of the proposed method in optimizing actuation costs.

Key words: tensegrity robots, optimization strategy, actuation cost, planetary exploration, PSO-BAS hybrid algorithm