Robots with joint elasticity find increasing interest in many research areas. A common design goal is to achieve as little mechanical joint damping as possible. To still achieve system damping often control systems are used. Here, we present a model-free approach to achieve damping via exploiting the kinetic to potential energy transformation process of the robot mass and the joint elasticity. The controller acts in an energetically passive way and is applicable to multi-joint systems. The theoretical findings and simulations are substantiated by experiments on the DLR Hand Arm System.

The elastic energy storage in biologically inspired variable impedance actuators (VIA) offer the capability of executing cyclic and/or explosive multi-degree of freedom (DoF) motions efficiently. This paper studies the generation of cyclic motions for strongly nonlinear underactuated multi-DoF serial robotic arms. By experimental observations of human motor control, a simple and robust control law is deduced. This controller achieves intrinsic oscillatory motions by switching the motor position triggered by a joint torque threshold. Using the derived controller, the oscillatory behavior of human and robotic arms is analyzed in simulations and experiments. It is found that the existence of easily excitable oscillation modes strongly depends on the damping properties of the plant. If the intrinsic damping properties are such that oscillations excited in the undesired modes decay faster than in the desired mode, then multi-DoF oscillations are easily excitable. Simulations and experiments reveal that serially-structured elastic multibody systems such as VIA or human arms with approximately equal joint damping, fulfill these requirements.

This paper presents a control approach to stabilize limit cycle motions along a mechanical mode of variable stiffness actuated (VSA) robots. Thereby, first a PD controller with gravity and Coriolis/centrifugal compensation shapes a desired dynamics, which is decoupled in terms of modal coordinates. Then an asymptotically stable limit cycle is generated on the link side dynamics for a selected mode. Finally, the modal control approach first introduced for rigid robots is extended to the VSA case. This is done by a joint torque controller, which decouples the torque dynamics from the link side dynamics. Stability and convergence are proven for the dynamics resulting from each feedback control. Furthermore, the energy efficiency of the proposed approach is verified by simulation and experiments on the VSA robotic arm DLR Hand Arm System.

Biologically inspired Variable Impedance Actuators (VIA) offer the capability to execute cyclic and/or explosive multi degree of freedom (DoF) motions efficiently by storing elastic energy. This paper studies the preconditions which allow to induce robust cyclic motions for strongly nonlinear, underactuated multi DoF robotic arms. By experimental observations of human motor control, a simple control law is deduced. This controller achieves intrinsic oscillatory motions by switching the motor position triggered by a joint torque threshold. Using the derived controller, the periodic behavior of the robotic arm is analyzed in simulations. It is found that a modal analysis of the linearized system at the equilibrium point allows to qualitatively predict the periodic behavior of this type of strongly nonlinear systems. The central statement of this paper is that cyclic motions can be induced easily in VIA systems, if the eigenfrequencies and modal damping values of the linearized system are well separated. Validation is given by simulation and experiments, where a human controls a simulated robotic arm, and the developed regulator controls a robotic arm in simulation and experiments.

Compliant actuators in robotic systems improve robustness against rigid impacts and increase the performance and efficiency of periodic motions such as hitting, jumping and running. However, in the case of rigid impacts, as they can occur during hitting or running, the system behavior is changed compared to free motions which turns the control into a challenging task. We introduce a controller that excites periodic motions along the direction of an intrinsic mechanical oscillation mode. The controller requires no model knowledge and adapts to a modal excitation by means of measurement of the states. We experimentally show that the controller is able to stabilize a hitting motion on the variable stiffness robot DLR Hand Arm System. Further, we demonstrate by simulation that the approach applies for legged robotic systems with compliantly actuated joints. The controlled system can approach different modes of motion such as jumping, hopping and running, and thereby, it is able to handle the repeated occurrence of robot-ground contacts.

Anthropomorphic robots that aim to approach human performance agility and efficiency are typically highly redundant not only in their kinematics but also in actuation. Variable-impedance actuators, used to drive many of these devices, are capable of modulating torque and impedance (stiffness and/or damping) simultaneously, continuously, and independently. These actuators are, however, nonlinear and assert numerous constraints, e.g., range, rate, and effort limits on the dynamics. Finding a control strategy that makes use of the intrinsic dynamics and capacity of compliant actuators for such redundant, nonlinear, and constrained systems is nontrivial. In this study, we propose a framework for optimization of torque and impedance profiles in order to maximize task performance, which is tuned to the complex hardware and incorporating real-world actuation constraints. Simulation study and hardware experiments 1) demonstrate the effects of actuation constraints during impedance control, 2) show applicability of the present framework to simultaneous torque and temporal stiffness optimization under constraints that are imposed by real-world actuators, and 3) validate the benefits of the proposed approach under experimental conditions.

Anthropomorphic robots that aim to approach human performance agility and efficiency are typically highly redundant not only in their kinematics but also in actuation. Variable-impedance actuators, used to drive many of these devices, are capable of modulating torque and passive impedance (stiffness and/or damping) simultaneously and independently. Here, we propose a framework for simultaneous optimisation of torque and impedance (stiffness) profiles in order to optimise task performance, tuned to the complex hardware and incorporating real-world constraints. Simulation and hardware experiments validate the viability of this approach to complex, state dependent constraints and demonstrate task performance benefits of optimal temporal impedance modulation.

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.

The concept of variable stiffness actuation (VSA) for robotic joints promises advantages regarding robustness, energy efficiency, and task adaptability. The VS joints developed at DLR show very low intrinsic damping for efficient energy storage and retrieval whereas the desired damping behavior for task execution needs to be implemented in control. Robotic arms with multiple VS joints, as for example the DLR Hand Arm System, ask for advanced control algorithms which can cope with the elastic joints and the multi-input multi-output (MIMO) system properties of the mechanical setup. We propose a MIMO controller for flexible joint robots based upon an eigenmode decoupling approach. For robustness reasons, the controller is designed to modify the intrinsic plant properties as little as possible while attaining the desired damping. A gain design algorithm is proposed. The controller is validated in simulations and experiments.

The DLR Hand Arm System is based upon the variable stiffness concept which has been recently developed to improve impact robustness and energy efficiency of modern robots. This paper continues the work on the bidirectional antagonistic variable stiffness (BAVS) joint concept which is an extension of antagonistic joints. Three mechanical setups utilizing different spring and cam disc combinations to implement a desired torque-stiffness characteristic are analyzed. Two BAVS joint solutions as used for the wrist and forearm rotation of the DLR Hand Arm System are presented. Furthermore in the experimental section torque-deflection calibration and drive redundancy are validated.

The variable stiffness actuation (VSA) technology has been recently developed and applied in robotic arms. Mechanism robustness, high peak torque and velocity, and stiffness adjustment flexibility are key benefits of VSA joints. However, the achievable Cartesian stiffness by uncoupled VSA joints is limited. Therefore we suggest and analyze the use of an active impedance controller in combination with the passive joints to further increase the stiffness range. An algorithm to optimize the passive and active Cartesian stiffness is proposed to achieve a desired Cartesian stiffness as precise as possible. The algorithm was implemented and tested on the VSA robot DLR Hand Arm System. Experimental results and measurements of the active/passive impedance algorithm are shown.

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.

The variable stiffness actuation concept is considered to provide a human-friendly robot technology. This paper examines a joint concept called the bidirectional antagonistic joint which is a extension of antagonistic joints. A new operating mode called the helping mode is introduced, which increases the joint load range. Although the joint can not be pretensioned in the helping mode, it is shown that a stiffness variation is possible, assuming a suitable torque-stiffness characteristic of the elastic elements. A methodology to design such characteristics is presented along with several example cases interpreted in a torque-stiffness plot. Furthermore, a stiffness adaptation control scheme which ensures mechanism safety is described. Finally, the design methodology and the control are evaluated on an implementation of a bidirectional antagonistic joint.