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Automatic Self-Calibration of Suspended Under-Actuated Cable-Driven Parallel Robot using Incremental Measurements

机译:使用增量测量自动自动校准悬浮的暂停电缆驱动的并联机器人

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This paper focuses on the problem of the initial-pose estimation by means of proprioceptive sensors (self-calibration) of suspended under- actuated Cable-Driven Parallel Robots (CDPRs). For this class of manipulators, the initialpose estimation cannot be carried out by means of forward kinematics only, but mechanical equilibrium conditions must be considered as well. In addition, forward kinematics solution is based on cable-length measurements, but if the robot is equipped with incremental sensors cables' initial values are unknown. In this paper, the self-calibration problem is formulated as a non-linear least square optimization problem (NLLS), based on the direct geometricostatic problem, where only incremental measurements on cable lengths and on swivel pulley angles are required. In addition, a data acquisition algorithm and an initial value selection procedure for the NLLS are proposed, aiming at automatizing the self-calibration procedure. Simulations and experimental results on a 3-cable 6-degree-of-freedom robot are provided so as to prove the effectiveness of the proposed methodology.
机译:本文侧重于悬浮型电缆驱动的并联机器人(CDPRS)的悬挂式传感器(自校准)初始姿势估计问题。对于这类操纵器,初始估计不能仅通过向前运动学进行,但也必须考虑机械平衡条件。此外,向前运动学解决方案基于电缆长度测量,但如果机器人配备有增量传感器,则电缆的初始值未知。在本文中,基于直接地形稳定问题,将自校准问题作为非线性最小二乘优化问题(NLLS),其中仅需要电缆长度和旋转皮带轮角上的增量测量。另外,提出了一种数据采集算法和NLL的初始值选择过程,旨在自动化自校准过程。提供了3缆线6-自由度机器人的模拟和实验结果,以证明提出的方法的有效性。

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