In this article, we propose a new algorithm for solving the forward dynamics of multibody systems consisting of rigid bodies connected in arbitrary topologies by localized joints and/or soft links, possibly actuated or not. The simulation is based on the implicit time integration of the Lagrangian model of these systems, where the soft links are modeled by Cosserat rods parameterized by assumed strain modes. This choice imposes a predictor–corrector structure on the approach, and requires computing both the residual vector and the Jacobian of the residual vector of the dynamics constrained by the time integrator. These additional calculations are handled here with a new Newton–Euler recursive inverse dynamics algorithm and its linearized tangent version. The approach is illustrated with numerical examples from the Cosserat rod literature and from recent robotic applications.

In the German Pavilion at the EXPO 2015, two large cable-driven parallel robots are flying over the heads of the visitors representing two bees flying over Germany and displaying everyday life in Germany. Each robot consists of a mobile platform and eight cables suspended by winches and follows a desired trajectory, which needs to be computed in advance taking technical limitations, safety considerations and visual aspects into account. In this paper, a path planning software is presented, which includes the design process from developing a robot design and workspace estimation via planning complex trajectories considering technical limitations through to exporting a complete show. For a test trajectory, simulation results are given, which display the relevant trajectories and cable force distributions.

Model based open-loop and closed-loop control systems make use of the system's inertial parameters. Unfortunately, not all of these values can be determined analytically nor can they be obtained from simple measurements. Established experiments for inertial parameters estimation have been applied to serial and parallel rigid-link manipulators, yet in very few cases to cable-driven parallel robots. Due to their kinematic properties and their unique setup, cable robots are more sensitive to incorrect estimates of the inertial parameters making it important to obtain such quantities through experiments. In this work, we assess the topic of inertial parameter identification of a parallel flexible-link manipulator exemplified by the suspended cable-driven parallel robot CoGIRo. Identification equations are derived from Newton-Euler equations of motion of an arbitrary point fixed to a rigid-body. Laboratory experiments for identification of the inertial parameters are then introduced and results are presented. Within the limitations of the sensors and data acquisition methods, reasonable results have been obtained, thereby validating the procedure for suspended cable-driven parallel robots.

Multi-stage production systems concede for low error and failure margins within every single machining and assembly step to not degrade product quality. Especially during multi-stage production of rotating parts, minor defects during a single step can corrupt a workpiece beyond repair. Since multistage production systems are complex, inter-connected chains of machining steps, a global approach to handling and compensating error emergence and propagation is for reaching Zero-Defect Manufacturing indispensable. We introduce Part Variation Modeling within a knowledge capturing platform to monitor centrally gathered metrological data for deviations. Further, a parametric model is presented allowing for description of rotating parts and enabling identification of deviations at every stage. Based on our inter-stage correlation analysis technique, the parametric model enables description of Part Variation Modes of a piece given current machine states and historic deviation likelihood as will be presented.