Directional singularity escape and avoidance for single-gimbal control moment gyroscopes

Despite the long history of studies on the singularity problem inherent to single-gimbal control moment gyroscopes, few existing gimbal steering laws can both accurately track moments and escape or avoid every type of singularity. The most-referenced steering laws perturb the system suboptimally at every singularity to enforce escape, which creates a tradeoff between minimizing escape time and minimizing transient tracking errors and gimbal rates. It is shown that no such tradeoff is necessary by proposing new singularity measures to quantify the current and future reference moment tracking capabilities and defining explicitly how an anticipated singularity can be avoided or escaped. Using these measures to separate and prioritize the tasks of moment tracking, gimbal damping, and singularity escape and avoidance, a gimbal steering law is designed that accurately tracks moments and avoids singularities when possible while escaping them with a minimal error moment otherwise. The steering law has smaller overall tracking errors and lower peak gimbal rates, and it achieves singularity escape faster than existing methods, as demonstrated analytically and using simulations.Accepted Author ManuscriptBiomechatronics & Human-Machine Contro

Influence of body weight unloading on human gait characteristics: A systematic review

Background: Body weight support (BWS) systems have shown promise as rehabilitation tools for neurologically impaired individuals. This paper reviews the experiment-based research on BWS systems with the aim: (1) To investigate the influence of body weight unloading (BWU) on gait characteristics; (2) To study whether the effects of BWS differ between treadmill and overground walking and (3) To investigate if modulated BWU influences gait characteristics less than unmodulated BWU. Method: A systematic literature search was conducted in the following search engines: Pubmed, Scopus, Web of Science and Google Scholar. Statistical analysis was used to quantify the effects of BWU on gait parameters. Results: 54 studies of experiments with healthy and neurologically impaired individuals walking in a BWS system were included and 32 of these were used for the statistical analysis. Literature was classified using three distinctions: (1) treadmill or overground walking; (2) the type of subjects and (3) the nature of unloading force. Only 27% studies were based on neurologically impaired subjects; a low number considering that they are the primary user group for BWS systems. The studies included BWU from 5% to 100% and the 30% and 50% BWU conditions were the most widely studied. The number of participants varied from 1 to 28, with an average of 12. It was seen that due to the increase in BWU level, joint moments, muscle activity, energy cost of walking and ground reaction forces (GRF) showed higher reduction compared to gait spatio-temporal and joint kinematic parameters. The influence of BWU on kinematic and spatio-temporal gait parameters appeared to be limited up to 30% unloading. 5 gait characteristics presented different behavior in response to BWU for overground and treadmill walking. Remaining 21 gait characteristics showed similar behavior but different magnitude of change for overground and treadmill walking. Modulated unloading force generally led to less difference from the 0% condition than unmodulated unloading. Conclusion: This review has shown that BWU influences all gait characteristics, albeit with important differences between the kinematic, spatio-temporal and kinetic characteristics. BWU showed stronger influence on the kinetic characteristics of gait than on the spatio-temporal parameters and the kinematic characteristics. It was ascertained that treadmill and overground walking can alter the effects of BWU in a different manner. Our results indicate that task-specific gait training is likely to be achievable at a BWU level of 30% and below.Correction to the article: http://resolver.tudelft.nl/uuid:87343b36-5c7d-4af8-8ab6-3e32d2e2c8d6Biomechatronics & Human-Machine Contro

Passive autonomy: Hygromorphic rotational actuators

Inspired by phenomena in the plant world, a meteoro-sensitive rotational actuator is developed. The design uses a hygro-active shell, whose water-based swelling is restricted at selective locations to form a helicoid structure. The influence of geometrical parameters on the performance is investigated using a numerical analysis of various geometries, by looking at resulting rotation and torque during this rotation. Prototypes are built of five key geometries in the design space, to validate the simulations and to investigate the behaviour of the design experimentally. These prototypes are submerged in water to investigate their deformation, after which they are placed in a torsion machine to investigate the torque during rotation. The experiments result in similar rotations and torques as the simulations. The designed Hygromorphic Rotational Actuator is capable of passively rotating its own structure, thereby expanding the possibilities of engineers and designers when designing passive autonomous systems.Mechatronic Systems DesignBiomechatronics & Human-Machine Contro

Reducing the energy consumption of robots using the bidirectional clutched parallel elastic actuator

Parallel elastic actuators (PEAs) have shown the ability to reduce the energy consumption of robots. However, regular PEAs do not allow us to freely choose at which instant or configuration to store or release energy. This paper introduces the concept and design of the bidirectional clutched parallel elastic actuator (BIC-PEA), which reduces the energy consumption of robots by loading and unloading a parallel spring with controlled timing and direction. The concept of the BIC-PEA consists of a spring that is mounted between the two outgoing axes of a differential mechanism. Those axes can also be locked to the ground by two locking mechanisms. At any position, the BIC-PEA can store the kinetic energy of a joint in the spring such that the joint is decelerated to zero velocity. The spring energy can then be released, accelerating the joint in any desired direction. Such functionality is suitable for robots that perform rest-to-rest motions, such as pick-and-place robots or intermittently moving belts. The main body of our prototype weighs 202 g and fits in a cylinder with a length of 51 mm and a diameter of 45 mm. This excludes the size and weight of the nonoptimized clutches, which would approximately triple the total volume and weight. In the results, we also omit the energy consumption of the clutches. The BIC-PEA can store 0.77 J and has a peak torque of 1.5 N.m. Simulations show that the energy consumption of our one-degree-of-freedom setup can be reduced by 73%. In hardware experiments, we reached peak reductions of 65% and a reduction of 53% in a realistic task, which is larger than all other concepts with the same functionality.Accepted Author ManuscriptOLD Biorobotic

Simulation of human gait with body weight support: benchmarking models and unloading strategies

BACKGROUND: Gait training with partial body weight support (BWS) has become an established rehabilitation technique. Besides passive unloading mechanisms such as springs or counterweights, also active systems that allow rendering constant or modulated vertical forces have been proposed. However, only pilot studies have been conducted to compare different unloading or modulation strategies, and conducting experimental studies is costly and time-consuming. Simulation models that predict the influence of unloading force on human walking may help select the most promising candidates for further evaluation. However, the reliability of simulation results depends on the chosen gait model. The purpose of this paper is two-fold: First, using human experimental data, we evaluate the accuracy of some of the most prevalent walking models in replicating human walking under the influence of Constant-Force BWS: The Simplest Walking model (SW), the Spring-Loaded Inverted Pendulum model (SLIP) and the Muscle-Reflex (MR) gait model. Second, three realizations of BWS, based on Constant-Force (CF), Counterweight (CW) and Tuned-Spring (TS) approaches, are compared to each other in terms of their influence on gait parameters. METHODS: We conducted simulations in Matlab/Simulink to model the behaviour of each gait model under all three BWS conditions. Nine simulations were undertaken in total and gait parameter response was analysed in each case. Root mean square error (mrmse) w.r.t human data was used to compare the accuracy of gait models. The metrics of interest were spatiotemporal parameters and the vertical ground reaction forces. To scrutinize the BWS strategies, loss of dynamic similarity was calculated in terms of root mean square difference in gait dynamics (Δgd) with respect to the reference gait under zero unloading. The gait dynamics were characterized by a dimensionless number Modela-w. RESULTS: SLIP model showed the lowest mrmse for 6 out of 8 gait parameters and for 1 other, the mrmse value were comparable to the MR model; SW model had the highest mrmse. Out of three BWS strategies, Tuned-Spring strategies led to the lowest Δgd values. CONCLUSIONS: The results of this work demonstrate the usefulness of gait models for BWS simulation and suggest the SLIP model to be more suitable for BWS simulations than the Simplest Walker and the Muscle-reflex models. Further, the Tuned-Spring approach appears to cause less distortions to the gait pattern than the more established Counterweight and Constant-Force approaches and merits experimental verification.Biomechatronics & Human-Machine Contro

Correction to: Influence of body weight unloading on human gait characteristics: A systematic review

Correction The original article [1] contained a major error whereby Fig. 1 mistakenly displayed a duplicate of Fig. 5. The correct version of Fig. 1 has now been restored and can be viewed ahead. Furthermore, this error was mistakenly introduced by the production team that handled this article and as such, was not the fault of the authors. (Figure Presented).Original article: http://resolver.tudelft.nl/uuid:2bb15cdc-7014-4efd-ad51-0dd6a2899675Influence of body weight unloading on human gait characteristics: A systematic review (Journal of NeuroEngineering and Rehabilitation (2018) 15 (53) DOI: 10.1186/s12984-018-0380-0)Biomechatronics & Human-Machine Contro

Role of trunk inertia in non-stepping balance recovery

Previous research has identified two major non-stepping strategies used to recover balance following mechanical perturbations: ankle and hip strategy [1, 2]. These strategies are selected depending on eg the perturbation magnitude, prior experience, and configuration of the support surface [2] in order to control the posture (upright trunk and leg orientation) and angular momentum [3, 4]. Following an external mechanical perturbation, both body posture and angular momentum depend, in part, on passive properties of the body, such as the amount and distribution of mass. Simple mechanical models, like the inverted pendulum (IP)[4, 5] or the double IP [6] suggest an approximately linear inverse relationship between the inertia of a perturbed body segment and the resultant acceleration and, presumably, also the segment deflection.Biomechatronics & Human-Machine Contro

Evaluation of physical damage associated with action selection strategies in reinforcement learning

Reinforcement learning techniques enable robots to deal with their own dynamics and with unknown environments without using explicit models or preprogrammed behaviors. However, reinforcement learning relies on intrinsically risky exploration, which is often damaging for physical systems. In the case of the bipedal walking robot Leo, which is studied in this paper, two sources of damage can be identified: fatigue of gearboxes due to backlash re-engagements, and the overall system damage due to falls of the robot. We investigate several exploration techniques and compare them in terms of gearbox fatigue, cumulative number of falls and undiscounted return. The results show that exploration with the Ornstein-Uhlenbeck (OU) process noise leads to the highest return, but at the same time it causes the largest number of falls. The Previous Action-Dependent Action (PADA) method results in drastically reduced fatigue, but also a large number of falls. The results reveal a previously unknown trade-off between the two sources of damage. Inspired by the OU and PADA methods, we propose four new action-selection methods in a systematic way. One of the proposed methods with a time-correlated noise outperforms the well-known e-greedy method in all three benchmarks. We provide guidance towards the choice of exploration strategy for reinforcement learning applications on real physical systems.Biomechatronics & Human-Machine ControlLearning & Autonomous Contro

Influence of internal oscillations on force sensing in coil springs

Coil springs are a common element in compliant actuators. For closed-loop control, the force of the coil spring has to be measured. Typically, deflection sensors indirectly measure this force. Implicitly, this assumes that the coil spring is a pure stiffness, without any mass. In reality, internal oscillations can occur due to impacts or other excitations of the spring’s resonance frequencies.This letter investigates the reliability of different force-sensing methods for coil springs that are oscillating internally. In addition to standard sensing via strain gauges or deflection sensors, also a new type of sensing is included, namely force estimation via the spring’s own electrical inductance. First, a lumped-mass model is used in simulations of three realistic conditions a coil spring mightbe subjected to in robotic applications. Second, a hardware experimentis conducted for one condition. Key effects predicted by the model are also found in the experiment, confirming the model’s validity. Results show that for all sensors, the increase in measuring uncertainty due to internal oscillations is of the same order of magnitude as typical sensors’ measuring uncertainty.Accepted Author ManuscriptBiomechatronics & Human-Machine ControlMechatronic Systems Desig

Reinforcement learning of potential fields to achieve limit-cycle walking

Reinforcement learning is a powerful tool to derive controllers for systems where no models are available. Particularly policy search algorithms are suitable for complex systems, to keep learning time manageable and account for continuous state and action spaces. However, these algorithms demand more insight into the system to choose a suitable controller parameterization. This paper investigates a type of policy parameterization for impedance control that allows energy input to be implicitly bounded: Potential fields. In this work, a methodology for generating a potential field-constrained impedance controller via approximation of example trajectories, and subsequently improving the control policy using Reinforcement Learning, is presented. The potential field-const rained approximation is used as a policy parameterization for policy search reinforcement learning and is compared to its unconstrained counterpart. Simulations on a simple biped walking model show the learned controllers are able to surpass the potential field of gravity by generating a stable limit-cycle gait on flat ground for both parameterizations. The potential field-constrained controller provides safety with a known energy bound while performing equally well as the unconstrained policy.Biomechatronics & Human-Machine ControlOLD Intelligent Control & RoboticsBiorobotic