In tendon-driven robotic hands, tendons are usually routed along several pulleys. The resulting friction is often substantial, and must therefore be modelled and estimated, for instance for accurate control and contact detection. Common approaches for friction estimation consider special dedicated setups, where the parameters of a static or dynamic friction model at a single contact point are determined. In this paper, we rather combine such individual friction models into an overall friction model for the entire finger. Furthermore, we propose a method for estimating the parameters of this overall model in situ, i.e. from trajectories executed on the assembled hand, avoiding the need for dedicated setups. An important component of the proposed model is a varying bias for treating friction at low velocities, allowing a simpler static friction model to be used. We demonstrate that our approach enables contacts to be detected more accurately on the DLR David hand, without additional sensors.

A physically-motivated friction model with a parametric description of the nonlinear dependency of the temperature and velocity as well as the dependency on external load is presented. The fully parametric approach extends a static friction model in the gross sliding regime. We show how it can be seamlessly integrated in standard dynamic friction models such as Lund Grenoble (LuGre) and Generalized-Maxwell-Slip (GMS). Parameters of a Harmonic Drive CSD 25 gear are experimentally identified and the final model is evaluated on a dedicated test-bed. We show the integration and effectiveness in dynamic simulation, friction compensation, and external torque estimation.

In robotic actuation a well identified and modeled friction behavior of the actuator components helps to significantly improve friction compensation, output torque estimation, and dynamic simulations. The friction of two components, i.e. a brush-less DC motor and a harmonic drive gear (HD) is investigated in order to build an accurate dynamic model of the main actuator of the arms of the humanoid David namely the DLR Floating Spring Joint (FSJ). A dedicated testbed is built to precisely identify input and output torques, temperatures, positions, and elasticities of the investigated components at a controlled environment temperature. Extensive test series are performed in the full velocity operating range in a temperature interval from 24 to 50 °C. The nonlinear influences of velocity and temperature are identified to be dominant effects. It is proposed how to include these nonlinear velocity and temperature dependencies into a static and a dynamic friction model, e.g. LuGre. Dynamic models of the motor and HD are built with the proposed method and experimentally evaluated. The new models are compared to friction models with linear dependencies and show a significant improvement of correspondence with reality.

Robots with Variable Stiffness Actuators (VSA) are intrinsically flexible in the joints. The built-in mechanical spring has the advantage of a higher peak performance, in some extend increased safety for humans interacting physically with the robot, and promises a more energy efficient robot for certain trajectories. This paper shows the modeling process of a VSA including energy losses on the example of the DLR Floating Spring Joint (FSJ). The model includes the full actuator dynamics with losses in electromechanical transformation of the motors. Furthermore, it models bearing and gear friction with stiction, Coulomb friction, viscous friction, and load dependent effects. With the obtained model the energy losses of benchmark trajectories are investigated and compared with a comparable stiff joint actuator.

Robots with Variable Stiffness Actuators (VSA) are intrinsically flexible in the joints. The built-in mechanical spring not only has the advantage of a higher peak performance, but also leads to a more robust robot. This paper presents and analyzes the threats to a VSA equipped robot that arise from external or internal origin. Influences of mechanical, moisture, electrical, thermal, radiation, and chemical nature are identified. Protection methods from these threats are discussed and the results presented. The results are separated into hardware, observation, control limiters, and reaction strategies. A hierarchical implementation of the control limiters and reaction strategies is presented. The reaction strategies use a motor position deviation and a change in the stiffness setup to reduce the load at high passive deflections in the VSA. Control limiter and reaction strategies have been implemented in the DLR Hand Arm System and evaluated experimentally with impacts on the system.

Intrinsically elastic robots, which technically implement some key characteristics of the human muskoskeletal system, have become a major research topic in nowadays robotics. These novel devices open up entirely new control approaches. They base on temporary storage of potential energy and its timed transformation into kinetic energy. In legged locomotion, such considerations have been a common tool for unveiling the respective fundamental physical processes. However, in arm control, elasticities were typically considered parasitic. In this video we outline our efforts in exploiting the inherent capabilities of intrinsically elastic robots in order to bring them closer to human performance. Instead of applying purely kinematic learing-by-demonstration approaches, which are certainly suboptimal, we argue for using model based techniques in order to optimally exploit the system dynamics such that highly dynamic motion and manipulation capabilities can be achieved. In particular, the explicit use of elasticities as temporary energy tanks can be fully exploited, if they are modeled adequately as an integral part of the mechanism. We also believe that such approaches can substantially contribute to the understanding of human motion biomechanics.

Most of today's robots have rigid structures and actuators requiring complex software control algorithms and sophisticated sensor systems in order to behave in a compliant and safe way adapted to contact with unknown environments and humans. By studying and constructing variable impedance actuators and their control, we contribute to the development of actuation units which can match the intrinsic safety, motion performance and energy efficiency of biological systems and in particular the human. As such, this may lead to a new generation of robots that can co-exist and co-operate with people and get closer to the human manipulation and locomotion performance than is possible with current robots.

An anthropomorphic hand arm system using variable stiffness actuation has been developed at DLR. It is aimed to reach its human archetype regarding size, weight and performance. The main focus of our development is put on robustness, dynamic performance and dexterity. Therefore, a paradigm change from impedance controlled, but mechanically stiff joints to robots using intrinsic variable compliance joints is carried out. Collisions of the rigid joint robot at high speeds with stiff objects induce the energy too fast for an active controller to prevent damages. In contrast, passively compliant robots are able to temporarily store energy. In this case the resulting internal forces applied to the robot structure and the drive trains are reduced. Furthermore, the energy storage allows to outperform the dynamics of stiff robots. The hand drives and the electronics are completely integrated within the forearm. Extremely miniaturized electronics have been developed to drive the 52 motors of the system and interface their sensors. Several variable stiffness actuation principles used in the arm joints and the hand are presented. The paper highlights the different requirements that they have to fulfill. A first test of the systems robustness and dynamics has been performed by driving nails with a grasped hammer and is demonstrated in the attached video.

Bringing mechanically compliant joints to robots is in the focus of interest world wide, especially in the humanoid robotics community. Variable Stiffness Joints (VSJ) promise to gain a high performing and robust robotic system. The presented DLR Floating Spring Joint (FSJ) is a VSJ module designed for the first 4 axes of the anthropomorphic DLR Hand Arm System. The DLR Hand Arm System aims to match the skills of its natural archetype. For this purpose, the joints have to be extremely compact to fit into the arm. At the same time they require a high power density in order to approximate the human arm skills. The new DLR FSJ is designed completely from an energy based point of view. This addresses not only energy efficient components and low friction design, but also that the potential energy of the spring is used as good as possible. A demonstration of robustness is given by the investigation of a blunt impact to the tip of the arm.

After briefly summarizing the mechanical design of the two joint prototypes for the new DLR variable compliance arm, the paper exemplifies the dynamic modelling of one of the prototypes and proposes a generic variable stiffness joint model for nonlinear control design. Based on this model, the design of a simple, gain scheduled state feedback controller for active vibration damping of the mechanically very weakly damped joint is presented. Moreover, the computation of the motor reference values out of the desired stiffness and position is addressed. Finally, simulation and experimental results validate the proposed methods.

Facing new tasks, the conventional rigid design of robotic joints has come to its limits. Operating in unknown environments current robots are prone to failure when hitting unforeseen rigid obstacles. Moreover, safety constraints are a major aspect for robots interacting with humans. In order to operate safely, existing robotic systems in this field are slow and have a lack of performance. To circumvent these limitations, a new robot joint with a variable stiffness approach (VS-Joint) is presented. It combines a compact and highly integrated design with high performance actuation. The VS- Joint features a highly dynamic stiffness adjustment along with a mechanically programmable system behavior. This allows an easy adaption to a big variety of tasks. A benefit of the joint is its intrinsic robustness against impacts and hard contacts, which permits faster trajectories and handling. Thus, it provides excellent attributes for the use in shoulder and elbow joints of an anthropomorphic robot arm.