Cable-Driven Parallel Robots (CDPR) employ extendable cables to control the pose of an end-effector (EE). If the number of cables is smaller than the degrees of freedom of the EE, and cables have no special arrangement reducing the EE freedoms, the robot is underactuated, and the EE is underconstrained: as a consequence, the EE preserves some freedoms even when all actuators are locked, which may lead to undesirable free motions. This paper proposes a novel methodology for the identification of the EE inertial parameters of these robots. Inertial parameters are useful, for example, in the application of feedforward control techniques. The main merit of our approach is that it does not require force or torque measurements, and only a subset of the robot kinematic variables needs to be measured. The method consists in the application of the EE internal-dynamics equations along a free-motion trajectory, also referred to as self-motion zero dynamics. This results in an over-determined system of equations that are linear in the EE inertial parameters (the Free-motion Internal-Dynamics Identification Model, FIDIM); the said system is solved according to the Total-Least-Square technique. Free-motion trajectories that are optimal for identification purposes are investigated and experimentally tested on a 4-cable robot. FIDIM is then applied, statistical analysis is performed, and the experimental results are cross-validated against additional free-motion trajectories.

电缆驱动并联机器人 ( CDPR ) 采用可伸缩电缆来控制末端执行器 ( EE )的姿态。如果电缆的数量比度的自由度较小的EE和电缆都没有特别的安排减少了EE自由，机器人欠驱动，而EE是欠约束：因此，在EE即使所有保留一些自由致动器被锁定，这可能导致不希望的自由运动。本文提出了一种识别EE的新方法这些机器人的惯性参数。例如，惯性参数在前馈控制技术的应用中很有用。我们方法的主要优点是它不需要测量力或扭矩，只需要测量机器人运动学变量的一个子集。该方法包括沿自由运动轨迹应用EE内部动力学方程，也称为自运动零动力学。这导致在EE惯性参数中线性的超定方程组（自由运动内部动力学识别模型，FIDIM); 所述系统是根据总最小二乘法求解的。在 4 电缆机器人上研究和实验测试了最适合识别目的的自由运动轨迹。然后应用FIDIM，执行统计分析，并针对额外的自由运动轨迹对实验结果进行交叉验证。