Soft robotic hands compensate for uncertainty in perception and actuation by leveraging passive deformation in their intrinsically compliant hardware, facilitating robust and dexterous interactions with their environment. The ability to adjust the level of compliance during operation has the potential to further improve the performance of these hands by enabling novel interaction strategies. However, achieving variable stiffness mechanically typically requires significant engineering complexity, making these systems difficult to manufacture, prone to error, and expensive. We present a novel, very simple mechanism for achieving variable stiffness. This mechanism employs tendon-driven antagonistic actuation, with Bowden cables connecting elastic elements to servomotors. It supports compact actuator designs, while the Bowden cables facilitate flexible component placement within a robotic system. Following our approach, variable stiffness actuators can be easily manufactured at low-cost from readily available materials. Despite its simplicity, we demonstrate that our mechanism provides consistent and precise control over stiffness levels and contact torques, showcasing its potential for a broad range of applications in soft robotic systems.

This study presents an innovative test rig engineered to explore the kinematic and viscoelastic characteristics of human specimen hands. The rig features eight force-controlled motors linked to muscle tendons, enabling precise stimulation of hand specimens. Hand movements are monitored through an optical tracking system, while a force-torque sensor quantifies the resultant fingertip loads. Employing this setup, we successfully demonstrated a pincer grip using a cadaver hand and measured both muscle forces and grip strength. Our results reveal a nonlinear relationship between tendon forces and grip strength, which can be modeled by an exponential fit. This investigation serves as a nexus between biomechanical and robotics-focused research, providing critical insights for the advancement of robotic hand actuation and therapeutic interventions.

Soft robots exhibit complex behaviors despite simple control, due to their inherently compliant hardware which passively deforms upon contact ± a concept commonly referred to as morphological computation. To fully determine the behavior of soft robots, not only their control software but also their passive behavior needs to be programmed. We show that deliberate programming of passive deformation in soft fingertips can significantly influence the grasping and manipulation performance of various robotic grippers. For this, the fingertips display strategically modulated compliance levels across their palmar surface, realized through adjustments to the local thickness of a lattice structure within their soft material, resulting in desired passive deformation. The grippers are operated by human participants, solving diverse tasks involving a variety of objects. We analyze 2025 human trials and show that the distinct passive behaviors programmed into the fingertips significantly affect grasping and manipulation performance. Furthermore, we discovered that specific compliance profiles consistently demonstrate superior performance, indicating that not merely inherent softness by itself, but a purposeful combination of varying compliance levels plays a pivotal role in successful soft interaction.

Injuries, accidents, strokes, and other diseases can significantly degrade the capabilities to perform even the most simple activities in daily life. A large share of these cases involves neuromuscular diseases, which lead to severely reduced muscle function. However, even though affected people are no longer able to move their limbs, residual muscle function can still be existent. Previous work has shown that this residual muscular activity can suffice to apply an EMG-based user interface. In this paper, we introduce DLR's robotic wheelchair EDAN (EMG-controlled Daily Assistant), which is equipped with a torque-controlled, eight degree-of-freedom light-weight arm and a dexterous, five-fingered robotic hand. Using electromyography, muscular activity of the user is measured, processed and utilized to control both the wheelchair and the robotic manipulator. This EMG-based interface is enhanced with shared control functionality to allow for efficient and safe physical interaction with the environment.

This paper presents the first two members of the new generation of CLASH hands, which exploit low cost actuation and rapid prototyping to create antagonistic modular and lightweight hands and grippers. The hands approach the robustness of the DLR Awiwi hand with a much lower complexity and cost. To reduce the number of required actuators, a differential coupling mechanism for underactuated fingers was developed, along with a new mechanism that uses variable stiffness actuation in order to increase the workspace of underactuated fingers. The hands provide a research platform for both hand-in-hand and robotic grasping. Design aspects are discussed, and an initial experimental validation verifies the hands' performance.

This paper examines the capability to incorporate spatial force feedback to the human toe when teleoperating a robotic arm in a force task. Due to the growing complexity of teleoperated systems new means of feedback get increasingly important. To investigate the viability of spatial toe-feedback, experiments with 12 subjects were conducted. The participants had to teleoperate a DLR Light-Weight Robot (LWR) via optical tracking of one finger in order to push a toy train. The orientation of the rail was unknown to the subject and had to be explored using the haptic feedback - a three-dimensional spatial force to the toe, reflecting the contact forces at the robotic end-effector - in absence of visual feedback. The rail was mounted in one of four possible orientations (differences of 45°). The main task of the experiment was to identify the present orientation. In our study subjects could successfully identify the orientation of the rail in more than two thirds of all trials (68%). In almost half of the trials (44%) the subjects were able to move the train along the rails long enough to reach the bumpers at the end and identify them as such. Assuming no feedback would be provided at all, the first metric has a chance level of 25%, and reaching the bumper can be considered impossible. Thus, we can conclude that humans can incorporate spatial force feedback to the toe into their sensorimotor loop.

Tool-held hitting tasks, like hammering a nail or striking a ball with a bat, require humans, and robots, to purposely collide and transfer momentum from their limbs to the environment. Due to the vibrational dynamics, every tool has a location where a hit is most efficient results in minimal tool vibrations, and consequently maximum energy transfer to the environment. In sports, this location is often referred to as the “sweet spot” of a bat, or racquet. Our recent neuroscience study suggests that humans optimize hits by using the jerk and torque felt at their hand. Motivated by this result, in this work we first analyze the vibrational dynamics of an end-effector-held bat to understand the signature projected by a sweet spot on the jerk and torque sensed at the end-effector. We then use this analysis to develop a controller for a robotic “baseball hitter”. The controller enables the robot-hitter to iteratively adjust its swing trajectory to ensure that the contact with the ball occurs at the sweet spot of the bat. We tested the controller on the DLR LWR III manipulator with three different bats. Like a human, our robot hitter is able to optimize the energy transfer, specifically maximize the ball velocity, during hits, by using its end effector position and torque sensors, and without any prior knowledge of the shape, size or material of the held bat.

A fundamental problem in human-robot collaboration is to ensure safety for humans being located in the workspace of the robot. Several new robots, referred to as collaborative robots, are pushing into the market. Most of these so-called co-bots have similar properties. They are small, lightweight and designed with big roundings to ensure safety in the case of a collision with a human. Equipped with torque sensors, external torque observers, tactile skins, etc., they are able to stop the robot when an emergency occurs. While developing more and more co-bots, the main focus lies on the robot itself. But to make a robot deployable, a special tool for a defined task is needed. These tools are often sharp-edged and dangerous in case of a collision with a human. In this paper we present a new safety module for robots to ensure safety for different tools in collaborative tasks. This module, filled with air pressure during the robot motion, covers mounted tools and carried workpieces. In case of a non or very slow moving robot, the safety module is able to pull back and the tool is uncovered. In our experiments we found out that we can increase the velocity up to 1 m/s while satisfying the requirements of the ISO/TS 15066 and retain the full functionality of the tool.

The most accurate and dependable approach to the in-vivo identification of human limb stiffness is by position perturbation. Moving the limb over a small distance and measuring the effective force gives, when states are steady, direct information about said stiffness. However, existing manipulandi are comparatively slow and/or not very stiff, such that a lumped stiffness is measured. This lumped stiffness includes the limb response during or after reflexes influenced by both, the passive musculotendon and active neuronal component. As this approach usually leads to inconsistencies between the data and the stiffness model, we argue in favour of fast, pre-reflex impedance measurements-i.e., completing the perturbation movement and collecting the data before effects of spinal reflexes or even from the motor cortex can influence the measurements. To obtain such fast planar movements, we constructed a dedicated orthoglide robot while focusing on a lightweight and stiff design. Our subject study of a force task with this device lead to very clean data with always positive definite Cartesian stiffness matrices. By representing them as ellipses, we found them to be substantially bigger in comparison to standard literature which we address to a larger number of recruited motor units. While ellipses orientation and the length of their main axis increased, the shape decreased with the exerted force. The device will be used to derive design criteria for variable-stiffness robots, and to investigate the relation between muscular activity and areflexive joint stiffness for teleoperational approaches.

We introduce a six-actuator robotic joint mechanism with biarticular coupling inspired by the human limb which neither requires pneumatic artificial muscles nor tendon coupling. The actuator can independently change monoarticular and biarticular stiffness as well as both joint positions. We model and analyse the actuator with respect to stiffness variability in comparison with an actuator without biarticular coupling. We demonstrate that the biarticular coupling considerably extends the range of stiffness with an 70-fold improvement in versatility, in particular with respect to the end-point Cartesian stiffness shape and orientation. We suggest using Cartesian stiffness isotropy as an optimisation criterion for future under-actuated versions.

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.

In this paper we present a novel and simple handheld device for measuring in vivo human grasp impedance. The measurement method is based on a static identification method and intrinsic impedance is identified inbetween 25 ms. Using this device it is possbile to develop continuous grasp impedance measurement methods as it is an active research topic in physiology as well as in robotics, especially since nowadays (bio-inspired) robotics can be impedance-controlled. Potential applications of human impedance estimation range from impedance-controlled telesurgery to limb prosthetics and rehabilitation robotics. We validate the device through a physiological experiment in which the device is used to show a linear relationship between finger stiffness and grip force.

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.