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 initial pose 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.
Ida E., Merlet J.-P., Carricato M. (2019). Automatic self-calibration of suspended under-actuated cable-driven parallel robot using incremental measurements. Cham : Springer Nature [10.1007/978-3-030-20751-9_28].
Automatic self-calibration of suspended under-actuated cable-driven parallel robot using incremental measurements
Ida E.;Carricato M.
2019
Abstract
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 initial pose 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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.