The flexibility and adaptability of modular and re-configurable robots opens up new opportunities for on-demand robot morphology optimization for varying tasks. In particular, multi-arm robotic systems can expand the solution space for any given task. In this paper, we present a novel approach to exploit this feature for generating optimal fit-to-task robot structures with respect to a minimum-effort objective. By describing the task in terms of relative poses between the end-effector and the constraint frame, and making use of the relative Jacobian, the minimum effort optimization problem can be equally expressed for single-arm or multi-arm robots. We test our approach for a peg-in-hole and a contour-following task and compare the performance of the optimal solution obtained with that of a standard manipulator configuration.

Torque distribution in redundant robots that combine the potential of asymmetric series-parallel actuated branches and multi-articulation pose a non-trivial challenge. To address the problem, this work proposes a novel optimization based controller that can accommodate various quadratic criteria to perform the torque distribution among dissimilar series and parallel actuators in order to maximize the motion efficiency. Three candidate criteria are composed and their performances are compared during periodic squat motions with a 3 degree of freedom series-parallel compliant articulated leg prototype. It is first shown that by minimizing a criterion that takes into account the actuator hardware specifications such as torque constant and transmission ratio, the gravity-driven phases can be lengthened. Thereby, this particular criterion results in slightly better performance than when adopting a strategy that maximizes the torque allocation to the higher efficiency actuators. Furthermore, valuable insights such as that the efficacy of maximum utilization of the highly-efficient parallel actuation branches decreases progressively at high frequencies were observed.

Linear Series Elastic Actuators exhibit a restricted design space. This inevitably leads to design trade-offs translating into robot performance limitations. These prevent robots from eventually reaching human comparable soft but also powerful physical interaction performance.This work presents a novel fixed passive rolling flexure design principle enabling the realization of a wide range of progressive torque-deflection characteristics. The proposed principle displays low hysteresis and can be manufactured in single 2D components. The paper derives the analytic foundation for the rolling flexure principle and is supported by numerical finite element analysis. The theory is validated by experimental results obtained on two laboratory prototypes.

This paper investigates the energy efficiency potential of continuously controllable clutches between the motors and links of robot joints. Inspired by biological muscles, the clutch enables free, purely gravity driven robot link motion phases gradually disengaged from gear friction, not requiring motor effort. The concept combines the energetic benefits of direct drives during unforced motion phases with the high torque density of conventional and mature geared robotic drive technology during forced motion phases. The paper specifies the general functional principle of the clutch for energy saving independent of any particular clutch implementation. The feasible energy saving of up to 60 % is investigated for harmonic link motions with varying frequencies and with respect to different ratios of link weight to friction torque. The outcomes of the theoretical investigations are supported by first experimental results.

In this paper, we present a novel global tracking control approach for elastic-joint robots that can be efficiently computed and is robust against model uncertainties and input disturbances. Elastic-joint robots provide enhanced safety and resiliency for interaction with the environment and humans. On the other hand, the joint elasticity complicates the motion-control problem especially when robust and precise trajectory tracking is required. Our proposed control approach allows us to merge the main benefits of the two well-known control schemes: inverse-dynamics (ID) control, which can be efficiently computed thanks to modern recursive algorithms, and passivity-based (PB) tracking control, which provides enhanced robustness to model uncertainty and external disturbances. As an extension of our previous work, we present a detailed robustness analysis of our combined ID/PB controller, a new variant of the original scheme that shows practically relevant implications, and finally, experimental results that verify the effectiveness of the approach.

We consider the global tracking control problem of robots with elastic joints. Even if joint elasticity introduces beneficial features for modern applications which require physically resilient and safer robots that can interact with the environment or humans, it challenges the achievable control performance. We propose a novel controller which combines the benefits of two approaches: the intrinsic robustness to model uncertainty from passivity-based control and the implementation efficiency of inverse-dynamics control schemes using a modern recursive algorithm. The novel controller is applied to an elastic-joint reconfigurable robotic arm using a recently proposed framework for on-the-fly control design. Simulation and experimental results validate our proposed approach.

Developing a high physical performance robotic manipulation platform with considerable power density, strength and resilience is not a trivial task and frequently leads to heavy and bulky systems unable to meet the application requirements, i.e. such robots should have human body size compatibility to work in infrastructures designed for humans. In this work we present a new high performance human size and weight compatible bi-manual manipulation platform that demonstrates notable physical strength and power capabilities. To attain this performance, design features including custom high performance elastic drives and robust light weight structure principles were considered resulting in large payload to robot mass ratio that is greater than 1.5 for short time heavy payloads. The design principles and mechanics of the upper body bi-manual robot are presented providing details on the solutions adopted for the various mechatronics components. The performance of the system actuation and the strength capacity of the overall platform is verified through the execution of heavy payload motion and impact experiments.

The paper proposes a method to assess the feasible torque bandwidth for electrically driven torque controllable actuators over its entire torque amplitude range. The method solely relies on the knowledge of hardware parameters and thereby determines the physically feasible torque control bandwidth at a given torque amplitude, independent of a controller. The method yields torque-frequency diagrams that are suitable to benchmark torque controllers, formulate actuator design specifications and compare as well as select actuators for a specific torque control application. The paper exemplifies the method on a WALK-MAN leg actuator with locked actuator output and the more practical case of a varying load inertia.

This contribution compares two approaches for applying disturbance observers (DOBs) to the torque control problem of series elastic actuators (SEAs). It is demonstrated that they are in fact equivalent for linear models in terms of their ability to reject disturbances and enforce nominal model dynamics. The closed loop and error transfer functions for the DOB-based approaches are compared to a fully linear plant and a nonlinear plant without DOB. Simulations demonstrate that the DOBs are able to increase the bandwidth of the nonlinear plant significantly, up to that of the linear plant. Furthermore, the DOBs significantly increase the tracking accuracy at low frequencies.

Link elasticity is commonly understood to be a detrimental side-effect of imperfect mechanical designs of robotic arms and comparable machinery. In contrast to this notion, this paper demonstrates a novel approach to exploit intrinsic robot link compliance in order to estimate a priori unknown payload masses, measure and also control end effector forces. In this way, the intrinsic link elasticity can be seen as an enabler for new sensing and control capabilities instead of a purely detrimental effect.

The infinite dimensionality, varying, uncertainties or even unknown boundary conditions render the derivation and - in particular - the identification of accurate dynamics models for elastic link robots tedious and error prone. This contribution circumvents these challenges by the prior application of a model-free inner loop oscillation damping controller before modelling the robot's dynamics. Then, the damped dynamics of a multi elastic link robot arm under gravity can be modelled with high accuracy. An analytical and a data-driven model for the damped dynamics are proposed and quantitatively compared. Both models can explain motor currents as well as link strain measurements in real-time. The paper includes an experimental model validation with different payloads in the entire workspace of the robot.

The paper experimentally compares six visual oscillation sensing approaches for a three degrees of freedom flexible link robot arm with an eye-in-hand RGB-D camera. The comparison includes five representative scenarios. Based upon the results the authors propose a novel scene adaptive camera motion reconstruction scheme. The scheme adaptively selects the best approach according to the actual scene texture and depth profile. Experiments in indoor scenarios with sparse texture, poor depth profiles as well as dynamic scene contents approve the obtained signal quality to be well suited for visual vibration damping of flexible link robot arms in a great variety of frequently observed scenarios.

Flexible, lightweight manipulators offer some advantages in contrast to rigid arms, such as compact and lighter drives, energy efficiency, reduced masses and costs. This paper presents a novel approach for vibration damping of a multi-link flexible arm. The strain of the elastic arms is measured with Fiber-Bragg-Grating (FBG) sensors and provides the feedback signal to dampen their flexural dynamics. A dynamic model of a three link arm is derived that accounts for the rigid and flexural dynamics including gravity. The arm vibrations are damped by nonlinear strain feedback. The controller is general and robust and its design does not require a model of the flexural dynamics. In the context of closed loop vibration control FBG sensors offer a better signal to noise ratio compared to strain gauges, which allows a higher static gain in the feedback loop with more efficient dissipation of vibrational energy. The feasibility and effectiveness of the proposed vibration control scheme in conjunction with FBG sensors is verified and analyzed in simulations and confirmed in experiments with a flexible three link robot arm.