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Non negative linear combination grasp force optimization

机译:非负线性组合抓力优化

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In order to improve the adaptability of multi-fingered grasp, a force optimization method was proposed to calculate the contact force of each finger, and an adaptive force tracking impedance control algorithm was designed to improve the compliance during contact. The force optimization was realized through a non-negative linear combination method for initial force calculation, combined with gradient algorithm to optimize the contact force. This method was put forward according to the property that the set of grasp force is a convex cone. First, the external force was decentralized as a linear combination of 12 unit force vectors, and then, the initial basic feasible solution for every unit force vector was calculated offline, at last, the initial value of the contact force was obtained by non-negative linear combination; based on the above calculation, the gradient algorithm was called to optimize the contact force online. The force-tracking impedance control method was applied by considering the contact compliance and the force-tracking precision. The indirect adaptive algorithm was applied to estimate the parameters of the object. Take the three fingered point contact with friction for example, the force can be optimized efficiently and the impedance algorithm can track the desired contact force with a relatively high accuracy.
机译:为了提高多指抓握的适应性,提出了一种力最优化方法来计算各根手指的接触力,并设计了一种自适应力跟踪阻抗控制算法,以提高接触时的顺应性。通过非负线性组合方法进行初始力计算,并结合梯度算法来优化接触力,从而实现了力的优化。根据抓握力为凸锥的性质提出了该方法。首先,将外力分散为12个单位力矢量的线性组合,然后,离线计算每个单位力矢量的初始基本可行解,最后,通过非负求出接触力的初始值线性组合基于上述计算,调用梯度算法在线优化接触力。考虑到接触顺应性和力跟踪精度,采用了力跟踪阻抗控制方法。间接自适应算法被应用于估计物体的参数。以摩擦的三指点接触为例,可以有效地优化力,并且阻抗算法可以以相对较高的精度跟踪所需的接触力。

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