Sensing Methods for Soft Robotics

Soft robots exhibit complex behaviors that emerge from deliberate compliance in the actuators and structure. This compliance allows soft robots to passively conform to the constraints of their environment and to the objects they are manipulating. Many soft robots are actuated by the flexible expansion of hermetically sealed volumes. Systems based on these principles are lightweight, flexible and have low reflected inertia. This makes them inherently safe in physical human robot interaction. Moreover, the sealed actuators and flexible joints are well-suited to work in harsh environments where external contaminates could breach the dynamic seals of rotating or sliding shafts. Accurate motion control remains a highly challenging task for soft robotic systems. Precise models of the actuation dynamics and environmental interactions are often unavailable. This renders open-loop control impossible, while closed-loop control suffers from a lack of suitable feedback. Conventional motion sensors, such as linear or rotary encoders, are difficult to adapt to robots that lack discrete mechanical joints. The rigid nature of these sensors runs contrary to the aspirational benefits of soft systems. Other proposed soft sensor solutions are still in their infancy and have only recently been used for motion-control of soft robots. This dissertation explores the design and use of inductance-based sensors for the estimation and control of soft robotic systems. These sensors are low-cost, lightweight, easy-to-fabricate and well-suited for the conditions that soft systems can best exploit. The inquiry of this dissertation is conducted both theoretically and experimentally for Fiber-Reinforced Elastomeric Enclosures (including McKibben muscles) and bellows actuators. The sensing of each actuator type is explored through models, design analyses and experimental evaluations. The results demonstrate that inductance-based sensing is a promising technology for these otherwise difficult-to-measure actuators. By combining sensing and actuation into a single component, the ideas presented in this work provide a simple, compact and lightweight way to create and control motion in soft robotic systems. This will enable soft systems that can interactively engage with their environment and their human counterparts.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/138590/1/wfelt_1.pd

"Body-In-The-Loop": Optimizing Device Parameters Using Measures of Instantaneous Energetic Cost

This paper demonstrates methods for the online optimization of assistive robotic devices such as powered prostheses, orthoses and exoskeletons. Our algorithms estimate the value of a physiological objective in real-time (with a body “in-the-loop”) and use this information to identify optimal device parameters. To handle sensor data that are noisy and dynamically delayed, we rely on a combination of dynamic estimation and response surface identification. We evaluated three algorithms (Steady-State Cost Mapping, Instantaneous Cost Mapping, and Instantaneous Cost Gradient Search) with eight healthy human subjects. Steady-State Cost Mapping is an established technique that fits a cubic polynomial to averages of steady-state measures at different parameter settings. The optimal parameter value is determined from the polynomial fit. Using a continuous sweep over a range of parameters and taking into account measurement dynamics, Instantaneous Cost Mapping identifies a cubic polynomial more quickly. Instantaneous Cost Gradient Search uses a similar technique to iteratively approach the optimal parameter value using estimates of the local gradient. To evaluate these methods in a simple and repeatable way, we prescribed step frequency via a metronome and optimized this frequency to minimize metabolic energetic cost. This use of step frequency allows a comparison of our results to established techniques and enables others to replicate our methods. Our results show that all three methods achieve similar accuracy in estimating optimal step frequency. For all methods, the average error between the predicted minima and the subjects’ preferred step frequencies was less than 1% with a standard deviation between 4% and 5%. Using Instantaneous Cost Mapping, we were able to reduce subject walking-time from over an hour to less than 10 minutes. While, for a single parameter, the Instantaneous Cost Gradient Search is not much faster than Steady-State Cost Mapping, the Instantaneous Cost Gradient Search extends favorably to multi-dimensional parameter spaces

A Compact Modular Soft Surface With Reconfigurable Shape and Stiffness

A variety of reconfigurable surface devices, utilizing large numbers of actuated physical pixels to produce discretized 3D contours, have been developed for different purposes in research and industry. The difficulty of integrating many actuators in close configuration has limited the DoF and resolution and performance of existing devices. Utilizing vacuum power and soft material actuators, we have developed a soft reconfigurable surface (SRS) with multi-modal control and performance capabilities. The SRS is comprised of a square grid array of linear vacuum-powered soft pneumatic actuators (linear V-SPAs), built into plug-and-play modules which enable the arrangement, consolidation, and control of many DoF. In addition to the practical benefits of system integration, this architecture facilitates the construction of customized assemblies with an overall compact form factor. A series of experiments is performed to illustrate and validate the versatility of the SRS for achieving diverse tasks including force controlled modulation of interface pressure through integrated sensors, lateral manipulation of a variety of objects, static and dynamic shape and pattern generation for haptic interaction, and variable surface stiffness tuning. This SRS concept is scalable, space efficient and features diverse functional potential. This will extend the utility and accessibility of tangible robotic interfaces for future applications from industrial to home and personal use

Folded-Tube Soft Pneumatic Actuators for Bending

This article presents a model and experimental results for a new class of bending soft pneumatic actuators (SPAs) made from a single section of thin-walled flexible tubing. The actuator is formed by creasing the tubing into fin-like rectangular folds and inserting the folds through regularly spaced slits in a high-strength fabric. When pressurized, the folds inflate and press against one another to create a bending moment. The actuator bends with a constant-length arc formed by the fabric. The walls of the tubing behave like an inextensible membrane. This membrane reinforcement allows the actuator to create large motions with limited material strain. Accordingly, the actuator can actuate over large bending angles without generating large elastic restoration forces in its structure. Spacing the slits for the folds closer together increases the bending moment for the same angle and pressure. Three folded-tube SPAs with different fold-spacings were experimentally characterized for this work. The strongest of the three was able to produce >190 N of tension and an estimated 10 Nm of bending moment with only 60 kPa. Even after bending 160 degrees, the bending moment was still similar to 5.7 Nm at the same pressure. The model presented in this work describes the moment per unit pressure of the actuators over the measured range of motion. For the 40 and 60 kPa tests, the model differed from the data with an average absolute error of <13% for all three actuators

Modeling Vacuum Bellows Soft Pneumatic Actuators with Optimal Mechanical Performance

This paper presents the concept and model of "Vacuum Bellows," a cylindrical membrane-reinforced contractile vacuum soft pneumatic actuator (V-SPAs). These actuators consist of a tubular membrane connected to a series of interior rigid rings periodically spaced along its length. Our model shows how the rings can be spaced to achieve a desired actuator force profile. For example, the contraction ratio can be maximized by spacing the rings one diameter apart inside the tube. The work output of the actuator can be concentrated in the initial portion of the stroke by increasing the ring spacing. And, usefully, an approximately constant force-to-pressure relationship can be created by spacing the rings a fraction of a diameter apart. Our experimental results highlight the utility of the model and some practical considerations for actuator fabrication and use. The experimental results demonstrate how the ring spacing can be used to achieve high peak forces per unit pressure (three times greater than an equivalent-diameter piston achieved experimentally) or large contractions (achieved contraction to 30% of the extended length). Our model suggests that this performance can be improved with improved fabrication techniques

Subject-Specific Data.

<p>The subject’s preferred cadence (step frequency) was evaluated while on a treadmill without a metronome. “Time constant” refers to the time constant of the metabolic response used in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0135342#pone.0135342.e008" target="_blank">Eq (1)</a>. This was characterized with a step-change in energetic requirements during the first six minutes of the Instantaneous Cost Mapping trial.</p

Examples of Response Surface Estimates of the Three Methods.

<p>Data are shown for Subject 1 and Subject 8 (poor and good performance of Instantaneous Cost methods respectively). This figure illustrates the third-order polynomial fit to the means (± SE) in the Steady-State Cost Mapping method, the third order polynomial response surface that best predicts the measures from the Instantaneous Cost Mapping, and the series of linear response surfaces used to update the parameter guess in the Instantaneous Cost Gradient Search (the lightening of shades indicates the sequence of the fits). The linear response surfaces of the Instantaneous Cost Gradient Search for Subject 1 show a much higher degree of variability than Subject 8. This led the algorithm to converge at a value somewhat below the subject’s preferred step frequency (worse than any other subject). Interestingly, the Instantaneous Cost Mapping for Subject 1 estimated a similarly low minimum. For subject 8, the linear response surfaces are more regular, leading the gradient search algorithm to outperform both of the mapping methods.</p

Qualitative Comparison of the Three Methods.

<p>SSCM refers to the traditional method of Steady-State Cost Mapping. Our methods rely on the estimation of Instantaneous Cost. ICM refers to the Instantaneous Cost Mapping and ICGS to the Instantaneous Cost Gradient Search.</p