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A unified quadratic-programming-based dynamical system approach to joint torque optimization of physically constrained redundant manipulators

机译:基于统一二次规划的动力系统方法,用于物理约束冗余机械臂的联合转矩优化

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In this paper, for joint torque optimization of redundant manipulators subject to physical constraints, we show that velocity-level and acceleration-level redundancy-resolution schemes both can be formulated as a quadratic programming (QP) problem subject to equality and inequality/bound constraints. To solve this QP problem online, a primal-dual dynamical system solver is further presented based on linear variational inequalities. Compared to previous researches, the presented QP-solver has simple piecewise-linear dynamics, does not entail real-time matrix inversion, and could also provide joint-acceleration information for manipulator torque control in the velocity-level redundancy-resolution schemes. The proposed QP-based dynamical system approach is simulated based on the PUMA560 robot arm with efficiency and effectiveness demonstrated.
机译:在本文中,对于受物理约束的冗余机械手的联合转矩优化,我们表明速度水平和加速度水平的冗余解决方案都可以表述为受等式和不等式/界线约束的二次规划(QP)问题。 。为了在线解决这个QP问题,基于线性变分不等式,进一步提出了原对偶动力系统求解器。与以前的研究相比,本文提出的QP解算器具有简单的分段线性动力学,不需要实时矩阵求逆,并且还可以为速度级冗余度解决方案中的机械手扭矩控制提供联合加速信息。在PUMA560机器人手臂的基础上,对所提出的基于QP的动力学系统方法进行了仿真,并证明了效率和有效性。

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