A suitable use of software packages for optimization problems can give the possibility to formulate design problems of robotic mechanical systems by taking into account the several aspects and behaviours for optimum solutions both in design and operation. However, an important issue that can be even critical to obtain practical solutions can be recognized in a proper identification and formulation of criteria for optimability purposes and numerical convergence feasibility. In this paper, we have reported experiences that have been developed at LARM in Cassino by referring to the abovementioned issues of determining a design procedure for manipulators both of serial and parallel architectures. The optimality criteria are focused on the well-recognized main aspects of workspace, singularity, and stiffness. Computational aspects are discussed to ensure numerical convergence to solutions that can be also of practical applications. In particular, optimality criteria and computational aspects have been elaborated by taking into account the peculiarity and constraint of each other. The general concepts and formulations are illustrated by referring to specific numerical examples with satisfactory results.
Characters with split personalities in Nessuno torna indietro by Alba de Céspedes and the German-Polish history of the novel – This paper focuses on the Polish reception of Nessuno torna indietro, a novel by Alba de Céspedes. In Italy the novel was a bestseller between 1938 and the eighties, however it was impossible to publish it in Poland due to the fact that negotiations failed. Nevertheless, the book was translated into Polish on the basis of the German version and published in a newspaper in 1947. The presentation of the Polish history of this novel will be based on archival materials.
Calibration is necessary for dual manipulator to complete operational tasks. This paper proposes an effective robot-robot and hand-eye calibration method based on virtual constraints. Firstly, a rotational error model and a translational error model are established based on the relationships between the transformation matrices of the dual manipulator calibration system. Then a poses-alignment method is designed to make the poses of the two robots satisfy the constructed virtual constraints. At the aligned positions, the joint angles of the two robots are saved and used to calculate the values of the variables in the error models. Finally, the robot-robot and hand-eye rotational errors are estimated by an iterative algorithm. These errors are then used to calculate translational errors based on the SVD (singular value decomposition) method. To show the feasibility and effectiveness of the proposed method, experiments of robot-robot and hand-eye calibration for dual manipulators are performed. The experiment results demonstrate that the accuracy of the dual manipulator system is improved greatly.
Iterative Learning Control (ILC) is a well-known method for control of systems performing repetitive jobs with high precision. This paper presents Constrained Output ILC (COILC) for non-linear state space constrained systems. In the existing literature there is no general solution for applying ILC to such systems. This novel method is based on the Bounded Error Algorithm (BEA) and resolves the transient growth error problem, which is a major obstacle in applying ILC to non-linear systems. Another advantage of COILC is that this method can be applied to constrained output systems. Unlike other ILC methods the COILC method employs an algorithm that stops the iteration before the occurrence of a violation in any of the state space constraints. This way COILC resolves both the hard constraints in the non-linear state space and the transient growth problem. The convergence of the proposed numerical procedure is proved in this paper. The performance of the method is evaluated through a computer simulation and the obtained results are compared to the BEA method for controlling non-linear systems. The numerical experiments demonstrate that COILC is more computationally effective and provides better overall performance. The robustness and convergence of the method make it suitable for solving constrained state space problems of non-linear systems in robotics.