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Optimal RRT* Planning and Synchronous Control of Cable-Driven Parallel Robots

机译:电缆驱动并联机器人的最佳RRT *规划和同步控制

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Cable-driven parallel robots (CDPRs) can provide high speed and heavy payload over large workspace by using multiple flexible cables. The main challenge of CDPRs stems from the motion control in which cables should avoid interferences and coordinate each other during the whole workspace. To solve it, a comprehensive motion control scheme including the optimal path planning and the synchronization control is proposed. Based on the improved Rapidly-exploring Random Tree (RRT*) algorithm, the path generation process with a novel cost function is presented to ensure the optimal path and the obstacle avoidance. Moreover, the Potential Field Guided (PFG) method is designed to further improve the efficiency of the planning algorithm. In order to validate that the moving platform can track the feasible path well, a synchronization controller is developed on the basis of the dynamic model. The simulations and experiments are implemented on a self-built 4-3 (4 cables with 3 DOF) CDPR. The results indicate that the proposed planning algorithm has much better efficiency than the RRT* algorithm, and the synchronization controller can get high tracking accuracy.
机译:电缆驱动的并行机器人(CDPR)可以通过使用多条柔性电缆在较大的工作空间中提供高速和重载。 CDPR的主要挑战来自运动控制,在整个工作空间中,电缆应避免干扰并相互协调。为了解决这个问题,提出了一种包括最优路径规划和同步控制的综合运动控制方案。基于改进的快速探索随机树(RRT *)算法,提出了一种具有新颖成本函数的路径生成过程,以确保最佳路径和避障。此外,设计了潜在场导(PFG)方法以进一步提高规划算法的效率。为了验证移动平台能够很好地跟踪可行路径,在动态模型的基础上开发了同步控制器。仿真和实验是在自建的4-3(4根电缆,3 DOF)CDPR上实现的。结果表明,所提出的规划算法比RRT *算法具有更高的效率,并且同步控制器可以获得较高的跟踪精度。

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