Pulleys and Force Sensors Influence on Payload Estimation of Cable-Driven Parallel Robots

Abstract

The subject of this paper is about the use of a suspended Cable-Driven Parallel Robot (CDPR) for pickand-place operations of heavy and heterogeneous objects. The knowledge of the payload mass and its center of mass in realtime is an asset for robust control of the device, which is required to ensure a good stability, especially when the objects have different shapes, sizes and masses. Accordingly, this paper aims at experimentally evaluating the effects of (i) the pulleys modeling and (ii) the use of force sensors for the payload estimation. It turns out that the consideration of the pulleys into the geometric model of the robot improves the mass and center of mass estimations of the payload. A comparison is made between the estimation of cable tensions from force sensors and from motor currents. Finally, a torque controller with a feedforward term for real-time mass compensation is proposed and implemented on a CDPR prototype.

Stiffness Oriented Tension Distribution Algorithm for Cable-Driven Parallel Robots

“…Similarly to the implementation of classical Tension Distribution Algorithms (TDAs) [12,15], the SOTDA is located in the control scheme after the sum of the control signal τ c and feedforward term τ da , as illustrated in Fig. 3.…”

Cable-driven parallel robot modelling considering pulley kinematics and cable elasticity

“…The CDPR have only the three Dof in position, the first CDPR is said to be non-redundant because it has 3 Dof for 3 cables, the other is redundant because for the same number of Dof it has 4 cables. In addition, the values of the necessary parameters for the definition of the CDPR are fixed close to those of the CAROCA CDPR of the IRT Jules Verne [31]. The CAROCA being the subject to numerous publications [5,32], its specifications are known.…”

Vision-Based Control and Stability Analysis of a Cable-Driven Parallel Robot

“…However, their accuracy should be substantially improved to meet a broader spectrum of industrial applications. In that sense, different approaches can be considered, such as the use of: (i) more precise, but more complex CDPR models [3]; (ii) force sensors to measure cable tensions [4]; (iii) angular position sensors to measure cable angle position [5]; and (iv) exteroceptive sensors, such as cameras, to measure where the robot is with respect to its environment [6] [7] [8].…”