The worldwide population aging and hence the higher risk of age‐related diseases facilitates interest in robotic devices for rehabilitation and movement assistance. A major factor of a persons functional independence is the ability to perform the movement task of standing up from a chair, also known as sit‐to‐stand (STS) movement. This work focuses on the development of a passive, wearable knee orthosis that supports the extension of the knee joint. As the knee flexes while sitting down a spring mechanism is loaded due to a cable wrapping around a deflection disc, thus generating a moment that assists standing up again. In order to prevent unintended knee extension this assistance moment should be minimized when the person is fully seated. To this end the geometry of the deflection disc, parametrized as B‐spline curve, is optimized in order to control the knee extension moment with respect to the knee angle. Initial tests with a first prototype show promising results.

In this paper an approach for robot force/position control combined with an iterative learning control is proposed. Following high speed force trajectories in different repetitive robotic applications is a challenging field in robotics. Such applications require a desired contact force while following a position/orientation trajectory in the non-force controlled directions. For this a parallel force/position control is suitable, but when it comes to high speed tasks with varying contact stiffness along the trajectory such a method reaches its dynamical limit. The problem can be solved by using the parallel force/position control to learn the trajectory for a slowed down task and correct this trajectory step by step towards the original task speed. When the original task speed is reached an iterative learning control law combined with the force/position control is used to further reduce the force error.

This paper proposes a learning robot force/position control for high speed force trajectory following. Following high speed force trajectories in different repetitve robotic applications is a challenging field in robot force control. If the end–effector should provide a contact force while following a position trajectory in the non–force controlled direction a parallel force / position control is suitable. However, when it comes to high speed tasks this force control method reaches its limit. The problem can be solved by using an iterative learning control method in combination with the parallel force/position control. In this paper the learning force control method is introduced and experimental results are presented. (© 2015 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim)

In this contribution two methods to increase the robustness of robot force control are discussed and experimental results on a real system are presented. One way to control end–effector forces of a robot is to use a force control method which manipulates the desired trajectory of a position controlled robot in a cascaded scheme. The benefit of this control scheme is that the end–effector is also able to follow position trajectories in the non–force–controlled directions. For such a direct parallel force/position control the stability depends on the force controller parameters and the contact stiffness, assuming a stable position control. Tuning these parameters in environments with varying contact stiffness is challenging and time consuming. To avoid this, additional feed–back torques are calculated to increase the dynamic of the force controller. The first method is based on the classical feed–forward control of a robotic system which is used in the feed–back loop of the force control. In the second method the acceleration term of the force control law is used to calculate a feed–back torque.

In this paper the effects of rotordynamics under the aspect of the choice of shape functions are discussed. For this purpose a rotor system which consists of a slim shaft and two rigid disks is modeled using the Projection Equation. The shaft is assumed as an elastic Euler-Bernoulli beam, supported by two bearings modeled as radial spring systems. The rotor is driven by a permanent-magnet synchronous motor whose torque is transmitted with a spur gear pair next to one of the bearings. A Ritz approach is used to separate the elastic displacements in position and time, thereby different shape functions are evaluated. Approximated eigenfunctions are computed and used as shape functions as well. For validation, the eigenfrequencies are compared with semianalytical ones, calculated with the Transfer-Matrix-Method and experimental results. The insights obtained from this work should make it easier to choose the appropriate shape functions for such problems.

AbstractFor many robotic applications with tasks such as cutting, assembly or polishing, it is necessary to get in contact with the surrounding. In this paper a redundant robot with seven degrees of freedom in a metal polishing task is considered. For simulation as well as for the controller design a dynamic model of the robot and a contact model are required. The equations of motion of the robot are calculated with the Projection Equation in subsystem representation and the contact model contains linear tool elasticities and work piece elasticities. In the case of a polishing task, a constant contact force during the process is required even if the robot moves along a trajectory. Thus some degrees of freedom of the robot tool center point have to be position controlled while the other ones have to be force controlled. The redundant robot offers the possibility to avoid singular positions or to maximize the available end‐effector forces within the inverse kinematics and is therefore best suited for polishing large objects. The actual process forces are measured with a six axis force‐torque‐sensor mounted at the tool center point. These forces are used in a parallel force/position control law to achieve the desired behavior. Results from measurements of a test arrangement are presented. (© 2014 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim)