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Elastic actuation taps into elastic elements' energy storage for dynamic motions beyond rigid actuation. While Series Elastic Actuators (SEA) and Variable Stiffness Actuators (VSA) are highly sophisticated, they do not fully provide control over energy transfer timing. To overcome this problem on the basic system level, the Bi-Stiffness Actuation (BSA) concept was recently proposed. Theoretically, it allows for full link decoupling, while simultaneously being able to lock the spring in the drive train via a switch-and-hold mechanism. Thus, the user would be in full control of the potential energy storage and release timing. In this work, we introduce an initial proof-of-concept of Bi-Stiffness-Actuation in the form of a 1-DoF physical prototype, which is implemented using a modular testbed. We present a hybrid system model, as well as the mechatronic implementation of the actuator. We corroborate the feasibility of the concept by conducting a series of hardware experiments using an open-loop control signal obtained by trajectory optimization. Here, we compare the performance of the prototype with a comparable SEA implementation. We show that BSA outperforms SEA 1) in terms of maximum velocity at low final times and 2) in terms of the movement strategy itself: The clutch mechanism allows the BSA to generate consistent launch sequences while the SEA has to rely on lengthy and possibly dangerous oscillatory swing-up motions. Furthermore, we demonstrate that providing full control authority over the energy transfer timing and link decoupling allows the user to synchronously release both elastic joint and gravitational energy. This facilitates the optimal exploitation of elastic and gravitational potentials in a synergistic manner., Comment: 8 pages, 9 figures. Submitted to IEEE Robotics and Automation Letters

This paper proposes a framework for generating fast, smooth and predictable braking manoeuvers for a controlled robot. The proposed framework integrates two approaches to obtain feasible modal limits for designing braking trajectories. The first approach is real-time capable but conservative considering the usage of the available feasible actuator control region, resulting in longer braking times. In contrast, the second approach maximizes the used braking control inputs at the cost of requiring more time to evaluate larger, feasible modal limits via optimization. Both approaches allow for predicting the robot's stopping trajectory online. In addition, we also formulated and solved a constrained, nonlinear final-time minimization problem to find optimal torque inputs. The optimal solutions were used as a benchmark to evaluate the performance of the proposed predictable braking framework. A comparative study was compiled in simulation versus a classical optimal controller on a 7-DoF robot arm with only three moving joints. The results verified the effectiveness of our proposed framework and its integrated approaches in achieving fast robot braking manoeuvers with accurate online predictions of the stopping trajectories and distances under various braking settings., Comment: This work has been accepted to the 22nd IFAC World Congress

Compliance in actuation has been exploited to generate highly dynamic maneuvers such as throwing that take advantage of the potential energy stored in joint springs. However, the energy storage and release could not be well-timed yet. On the contrary, for multi-link systems, the natural system dynamics might even work against the actual goal. With the introduction of variable stiffness actuators, this problem has been partially addressed. With a suitable optimal control strategy, the approximate decoupling of the motor from the link can be achieved to maximize the energy transfer into the distal link prior to launch. However, such continuous stiffness variation is complex and typically leads to oscillatory swing-up motions instead of clear launch sequences. To circumvent this issue, we investigate decoupling for speed maximization with a dedicated novel actuator concept denoted Bi-Stiffness Actuation. With this, it is possible to fully decouple the link from the joint mechanism by a switch-and-hold clutch and simultaneously keep the elastic energy stored. We show that with this novel paradigm, it is not only possible to reach the same optimal performance as with power-equivalent variable stiffness actuation, but even directly control the energy transfer timing. This is a major step forward compared to previous optimal control approaches, which rely on optimizing the full time-series control input., Comment: Accepted version of article that has been published in 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

The current technical specification ISO/TS15066:2016(E) for safe human-robot interaction contains logically conflicting definitions for the contact between human and robot. This may result in different interpretations for the contact classification and thus no unique outcome can be expected, which may even cause a risk to the human. In previous work, we showed a first set of implications. This paper addresses the possible interpretations of a collision scenario as a result of the varying interpretations for a risk assessment. With an experiment including four commercially available robot systems we demonstrate the procedure of the risk assessment following the different interpretations of the TS. The results indicate possible incorrect use of the technical specification, which we believe needs to be resolved in future revisions. For this, we suggest tools in form of a decision tree and constrained collision force maps, which enable a simple, unambiguous risk assessment for HRI.

In robotics, many control and planning schemes have been developed to ensure human physical safety in human-robot interaction. The human psychological state and the expectation towards the robot, however, are typically neglected. Even if the robot behaviour is regarded as biomechanically safe, humans may still react with a rapid involuntary motion (IM) caused by a startle or surprise. Such sudden, uncontrolled motions can jeopardize safety and should be prevented by any means. In this letter, we propose the Expectable Motion Unit (EMU), which ensures that a certain probability of IM occurrence is not exceeded in a typical HRI setting. Based on a model of IM occurrence generated through an experiment with 29 participants, we establish the mapping between robot velocity, robot-human distance, and the relative frequency of IM occurrence. This mapping is processed towards a real-time capable robot motion generator that limits the robot velocity during task execution if necessary. The EMU is combined in a holistic safety framework that integrates both the physical and psychological safety knowledge. A validation experiment showed that the EMU successfully avoids human IM in five out of six cases.

Falls and their related injuries pose a significant risk to human health. One of the most common falls, the forward fall, frequently occurs among adults and the elderly. In this study, we propose using a human body model, developed using the MAthematical DYnamic MOdel (MADYMO) software, in place of human subjects, to investigate forward fall-related injuries. The MADYMO human body model is capable of simulating items that cannot be assessed on human subjects, such as human kinematics, human dynamics, and the possibility of injuries. In order to achieve our goal, a set of experiments was conducted to measure the impact force during a worst-case forward fall scenario (the outstretched hand position) for two short fall heights. Similar to the experimental design used on the human subjects, we generated a MADYMO human model. After performing the simulations, the results of the experiment on the human subjects and the MADYMO simulation model were compared. We demonstrated a significant correlation between the MADYMO simulation and the human subject experiments with respect to the magnitude and timing of the impact forces. Consequently, we validated the MADYMO human body model as a means to accurately assess forward fall-related injuries. Additionally, we compared the predicted results of a mathematical model with the MADYMO human body model. The MADYMO model is reliable and can demonstrate an accurate impact time. Therefore, we conclude that the MADYMO human model can be utilized as a reliable model to investigate forward fall-related injuries from a typical standing position.

The biomechanical studies have proposed several forward fall arresting strategies to reduce the impact forces in a human-robot collaboration environment. A proposed strategy is using a compliant flooring for an environment because it can reduce the stiffness of the ground. In this study, we proposed that if a rigid layer is mounted on a compliant flooring (double-layer flooring), the impact force is further reduced. In order to investigate this goal, we designed two subjective laboratory experiments. In experiment 1, the subjects were instructed falling to the ground where was covered by a single layer of compliant material (a foam pad). In experiment 2, the subjects fell on double-layer flooring when one rigid layer (a wood surface) was mounted on the compliant layer. The impact forces were measured for two short forward fall heights onto the outstretched hand. The results showed that the profile of the impact forces consists of two peaks. The first peak has a higher magnitude, and it is followed by the second peak with a lower magnitude. Comparing the magnitude of the first peak between two experiments shows a reduction of the impact force in experiment 2. In contrast, the magnitudes of second peaks are identical for both experiments. Therefore, we concluded that using a double-layer flooring, i.e.one rigid layer and one compliant layer can be an effective strategy for considerably reducing the impact force, and preventing the wrist fractures during the forward fall.