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Inverse Statics Optimization for Compound Tensegrity Robots

机译:复合态变形机器人的逆静态优化

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Robots built from cable-driven tensegrity ('tension-integrity') structures have many of the advantages of soft robots, such as flexibility and robustness, yet still obey simple statics and dynamics models. However, existing approaches cannot natively model tensegrity robots with arbitrary rigid bodies in their tension network. This work presents a method to calculate the cable tensions in static equilibrium for such robots, here defined as compound tensegrities. First, a static equilibrium model for compound tensegrity robots is reformulated from the standard force density method used with other tensegrity structures. Next, we pose the problem of calculating tension forces in the robot's cables under our model. A solution is proposed as a quadratic optimization problem with practical constraints. Simulations illustrate how this inverse statics optimization problem can be used for both the design and control of two different compound tensegrity applications: a spine robot and a quadruped robot built from that spine. Finally, we verify the accuracy of the inverse statics model through a hardware experiment, demonstrating the feasibility of low-error open-loop control using our methodology.
机译:从电缆驱动的矩形(“张力 - 完整性”)结构构建的机器人具有许多软机器人的优点,例如灵活性和鲁棒性,但仍然遵守简单的静态和动力学模型。然而,现有方法不能在其张力网络中自然地模拟具有任意刚体的矩形机器人。这项工作提出了一种方法来计算这种机器人的静态平衡中的电缆张力,这里定义为复合态。首先,从与其他牙态结构一起使用的标准力密度法重新重新重整化复合矩形机器人的静态平衡模型。接下来,我们在模型下计算了机器人电缆中的张力力的问题。提出了一种解决方案作为具有实际限制的二次优化问题。模拟说明了这种逆静态优化问题的设计和控制如何用于两种不同的复合技术的设计和控制:脊柱机器人和从该脊柱构建的四足机器人。最后,我们通过硬件实验验证了逆静音模型的准确性,展示了使用我们的方法的低误差开环控制的可行性。

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