Compliant and precise rotary drive units are essential for the design of articulated robots that are capable of safe human-robot collaboration. In this paper, we present a new pneumatic rotary drive unit that combines the compliance of pneumatic systems with the ability to perform high precision positioning. We use pneumatic artificial muscles (PAMs) pulling on a swash plate to avoid the stick-slip phenomenon and to realize adjustable stiffness. Furthermore, the presented drive unit can operate in 360° continuous rotation. These properties make the drive particularly suitable for the later use in human-robot collaboration. We explain the mechanic design as well as the pneumatic and electric control system that we use to operate the drive unit. We derive the equations to calculate the static torque distribution and compare the theoretical results to the data measured on the realized laboratory test stand, depicted in figure 1. The accuracy of the used 16-bit encoder is achieved and adjustable stiffness is realized and measured on the laboratory test stand. The measurements of the reaction to a step response are discussed based on a first and basic control strategy.

Recent intuitive robot programming approaches operate on task level, enabling programmers to intuitively arrange or compose encapsulating robot capabilities (skills). This paper presents an approach to intuitively create (sub-)skills. General guidelines for assembly process descriptions #2860 provided by the Association of German Engineers VDI are applied to robot programming, in particular addressing assembly applications. The guidelines are exemplarily applied to the constraint-based approach iTaSC (instantaneous Task Specification using Constraints), presenting a procedure to hierarchically combine elementary processes to (sub-)skills. Six elementary processes are identified to be sufficient to implement a wide variety of assembly tasks. An iTaSC implementation was developed and two exemplarily assembly tasks were realized to evaluate the approach.

In recent years, a number of publications described approaches for model-based manipulation skills and their applicability to a variety of robot tasks-be it assembly, industrial robotics in general, or service robotics. These approaches roughly follow the same pattern: They model robot task description based on the Task Frame Formalism, the Task Function Approach, or iTaSC. They model coordination mechanisms in form of statecharts or Petri nets. And almost all models are accompanied by domain-specific languages (DSLs) that facilitate creating applications based on those models. While one advantage of using models is their reusability across applications, how to explicitly model the reuse itself has not been fully addressed by these publications. Our paper contributes to this field of research by investigating how reuse can be explicitly modeled using prototype-based inheritance. We base our model on iTaSC and provide a simple yet effective DSL for populating the model and creating applications. We demonstrate our approach by creating a comprehensive library of skills, and by showing the use, reuse and incremental refinement of skills for diverse industrial assembly applications.

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.

Cable-driven parallel robots, hereinafter referred to as cable robots, use cables to manipulate a mobile platform with 6 DOF. Cable robots have a low moved mass, as the winches with the servo drives are fixed to the machine frame and light weight synthetic fiber cables can be used. Therefore, cable robots are assumed to have a good energy efficiency. To analyze the energy efficiency in detail, we establish an energy consumption model for a cable robot and parametrize it for the cable robot IPAnema 3. Losses in the mechanical parts like winches as well as electrical losses in the servo amplifier and recuperation effects are taken into account. The analysis of the energy consumption shows that the mechanical losses are dominant. The losses occur especially during movement of the robot while the energy needed for statically balancing the load is quite low. We can experimentally determine a maximum winch efficiency of 85%. For dimensioning the drive, one has to add approximately one third of the torque to account for the friction in the mechanics. In a fully-constrained cable robot, the energy consumption can be influenced by the internal tension in a range of 20%. We also compare the energy efficiency of the cable robot with an industrial robot. The comparison shows, that both robots consume almost the same amount of energy.

Workspace determination for robots is an important step in analysis and synthesis. A couple of methods for computing the wrench-closure workspace of cable-driven parallel robots were reported in the literature but all methods tend to be time consuming. In this paper, a new algorithm is presented that exploits different techniques to speed up the computation. Pre-computation is largely exploited and benefit are gained both from considerations in computer algebra and efficient numerical routines. Results from the computation of the translational (sometimes also called constant orientation) wrench-closure workspace are presented and performance values are provided. To the best of the authors' knowledge, the method proposed in this paper is superior in terms of computational time to any other approach for workspace computation.

This paper introduces the CableRobot simulator, which was developed at the Max Planck Institute for Biological Cybernetics in cooperation with the Fraunhofer Institute for Manufacturing Engineering and Automation IPA. The simulator is a completely novel approach to the design of motion simulation platforms in so far as it uses cables and winches for actuation instead of rigid links known from hexapod simulators. This approach allows to reduce the actuated mass, scale up the workspace significantly, and provides great flexibility to switch between system configurations in which the robot can be operated. The simulator will be used for studies in the field of human perception research and virtual reality applications. The paper discusses some of the issues arising from the usage of cables and provides a system overview regarding kinematics and system dynamics as well as giving a brief introduction into possible application use cases.

In a cable-driven parallel robot, elastic cables are used to manipulate the end effector within the workspace. Cable force measurement is necessary for several control algorithms like cable force control, contact control, or load identification. The cable force sensor can be placed directly at the connection point on the platform or somewhere along the cable using pulleys. The pulleys between the force sensor and the platform disturb the force measurement accuracy due to friction. This paper deals with modeling and compensation of the friction. The friction behavior in the drive train with focus on the effects of the pulleys is non-trivial, as the cable movement consists of microscopic and macroscopic movements and standstills. Friction models from Coulomb and Dahl are adapted to deal with the pulley friction. The experimental evaluation showed an improvement of 70% with respect to the uncompensated case.

Most cable-driven parallel robots are kinematically over-constrained mechanisms. This results in a non-trivial computation of the forward kinematic transformation. It is well known that the forward kinematics of parallel robots may have multiple solutions and in general the convergence of numerical methods is unknown. In recent works, it was proposed to formulate the forward kinematics as optimization problem that models the cables as linear springs in order to compute the platform pose which has minimal potential energy in the cables. In this paper, we analyzed this objective function. Using the Hessian matrix, we show that under certain conditions the problem at hand is convex and we can expect a unique and stable minimum. The computations are exemplified for point-shaped platforms as well as for the planar case. For the spatial case, we present an encouraging numerical study. An ordinary least squares method is then applied to find a position approximation and an improvement to previous methods is demonstrated.

In a cable-driven parallel robot, elastic cables are used to manipulate the end effector in the workspace. In this paper we present a dynamic analysis and system identification for the complete actuator unit of a cable robot including servo controller, winch, cable, cable force sensor and field bus communication. We establish a second-order system with dead time as an analagous model. Based on this investigation, we propose the design and stability analysis of a cable force controller. We present the implementation of feed-forward and integral controllers based on a stiffness model of the cables. As the platform position is not observable the challenge is to control the cable force while maintaining the positional accuracy. Experimental evaluation of the force controller shows, that the absolute positional accuracy is even improved.

In Cable-Driven parallel robots, elastic cables are used to control the movement of a platform in the workspace. The accuracy of a robot system is one of the most important comparison criteria for various applications. In this paper, we present a new approach to increase the relative accuracy of a cable robot under changing payload, by compensating the error induced by elasticity. In the first step, the load is identified based on cable force sensors and the acceleration of the platform. Second, for the actual pose the stiffness matrix is computed and the expected displacement of the platform in Cartesian space is determined. Lastly, the displacement is compensated by adapting the cable lengths. Furthermore, the influence of the calibration of cable force sensors and their parameters' inaccuracies are discussed. The algorithms are implemented and evaluated on a 6-DOF cable robot. We could experimentally prove an improvement of over 50% in the relative accuracy under changing load.

Currently, pseudo-omnidirectional, wheeled mobile robots with independently steered and driven wheels seem to provide a solid compromise between complexity, flexibility and robustness. Yet, such undercarriages are imposed to the risk of actuator fighting and suffer from singular regions within their configuration space. To address these problems we expand a previously developed potential field (PF) based approach by expanding it with a predictive horizon. The proposed method is based on a model predictive control (MPC) approach, incorporating a gradient descent optimization step via the Pontryagin minimum principle. To enforce adherence to the constraints during optimization, we modify the Lagrange-multipliers within the backpropagation of the costates. The proposed approach is evaluated simulatively w.r.t. the undercarriage of the Care-O-bot®3 mobile robot and is compared to the potential field based and a model predictive control approach.