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Embedded 3D Printing of Strain Sensors within Highly Stretchable Elastomers

A new method, embedded-3D printing (e-3DP), is reported for fabricating strain sensors within highly conformal and extensible elastomeric matrices. e-3DP allows soft sensors to be created in nearly arbitrary planar and 3D motifs in a highly programmable and seamless manner. Several embodiments are demonstrated and sensor performance is characterized.

Waalbot II: Adhesion Recovery and Improved Performance of a Climbing Robot using Fibrillar Adhesives

This paper presents the design and optimization of a wall-climbing robot along with the incorporation of autonomous adhesion recovery and a motion planning implementation. The result is Waalbot II, an untethered 85 g robot able to climb on smooth vertical surfaces with up to a 100 g payload (117% body mass) or, when unburdened, on planar surfaces of any orientation at speeds up to 5 cm/s. Bio-inspired climbing mechanisms, such as Waalbot II’s gecko-like fibrillar adhesives, passive peeling, and force sensing, improve the overall climbing capabilities compared with initial versions, resulting in the ability to climb on non-smooth surfaces as well as on inverted smooth surfaces. Robot length scale optimization reveals and quantifies trends in the theoretical factor of safety and payload carrying capabilities. Autonomous adhesion recovery behavior provides additional climbing robustness without additional mechanical complexity to mitigate degradation and contamination. An implementation of a motion planner, designed to take into account Waalbot II’s kinematic constraints, results in the ability to navigate to a goal in complex three-dimensional environments while properly planning plane-to-plane transitions and avoiding obstacles. Experiments verified the improved climbing capabilities of Waalbot II as well as its novel semi-autonomous adhesion recovery behavior and motion planning.

Wearable soft sensing suit for human gait measurement

Wearable robots based on soft materials will augment mobility and performance of the host without restricting natural kinematics. Such wearable robots will need soft sensors to monitor the movement of the wearer and robot outside the lab. Until now wearable soft sensors have not demonstrated significant mechanical robustness nor been systematically characterized for human motion studies of walking and running. Here, we present the design and systematic characterization of a soft sensing suit for monitoring hip, knee, and ankle sagittal plane joint angles. We used hyper-elastic strain sensors based on microchannels of liquid metal embedded within elastomer, but refined their design with the use of discretized stiffness gradients to improve mechanical durability. We found that these robust sensors could stretch up to 396% of their original lengths, would restrict the wearer by less than 0.17% of any given joint’s torque, had gauge factor sensitivities of greater than 2.2, and exhibited less than 2% change in electromechanical specifications through 1500 cycles of loading–unloading. We also evaluated the accuracy and variability of the soft sensing suit by comparing it with joint angle data obtained through optical motion capture. The sensing suit had root mean square (RMS) errors of less than 5° for a walking speed of 0.89 m/s and reached a maximum RMS error of 15° for a running speed of 2.7 m/s. Despite the deviation of absolute measure, the relative repeatability of the sensing suit’s joint angle measurements were statistically equivalent to that of optical motion capture at all speeds. We anticipate that wearable soft sensing will also have applications beyond wearable robotics, such as in medical diagnostics and in human–computer interaction.

Soft wearable motion sensing suit for lower limb biomechanics measurements

Motion sensing has played an important role in the study of human biomechanics as well as the entertainment industry. Although existing technologies, such as optical or inertial based motion capture systems, have relatively high accuracy in detecting body motions, they still have inherent limitations with regards to mobility and wearability. In this paper, we present a soft motion sensing suit for measuring lower extremity joint motion. The sensing suit prototype includes a pair of elastic tights and three hyperelastic strain sensors. The strain sensors are made of silicone elastomer with embedded microchannels filled with conductive liquid. To form a sensing suit, these sensors are attached at the hip, knee, and ankle areas to measure the joint angles in the sagittal plane. The prototype motion sensing suit has significant potential as an autonomous system that can be worn by individuals during many activities outside the laboratory, from running to rock climbing. In this study we characterize the hyperelastic sensors in isolation to determine their mechanical and electrical responses to strain, and then demonstrate the sensing capability of the integrated suit in comparison with a ground truth optical motion capture system. Using simple calibration techniques, we can accurately track joint angles and gait phase. Our efforts result in a calculated trade off: with a maximum error less than 8%, the sensing suit does not track joints as accurately as optical motion capture, but its wearability means that it is not constrained to use only in a lab.

Staying sticky: contact self-cleaning of gecko-inspired adhesives.

The exceptionally adhesive foot of the gecko remains clean in dirty environments by shedding contaminants with each step. Synthetic gecko-inspired adhesives have achieved similar attachment strengths to the gecko on smooth surfaces, but the process of contact self-cleaning has yet to be effectively demonstrated. Here, we present the first gecko-inspired adhesive that has matched both the attachment strength and the contact self-cleaning performance of the geckos foot on a smooth surface. Contact self-cleaning experiments were performed with three different sizes of mushroom-shaped elastomer microfibres and five different sizes of spherical silica contaminants. Using a load–drag–unload dry contact cleaning process similar to the loads acting on the gecko foot during locomotion, our fully contaminated synthetic gecko adhesives could recover lost adhesion at a rate comparable to that of the gecko. We observed that the relative size of contaminants to the characteristic size of the microfibres in the synthetic adhesive strongly determined how and to what degree the adhesive recovered from contamination. Our approximate model and experimental results show that the dominant mechanism of contact self-cleaning is particle rolling during the drag process. Embedding of particles between adjacent fibres was observed for particles with diameter smaller than the fibre tips, and further studied as a temporary cleaning mechanism. By incorporating contact self-cleaning capabilities, real-world applications of synthetic gecko adhesives, such as reusable tapes, clothing closures and medical adhesives, would become feasible.

Toward a modular soft sensor-embedded glove for human hand motion and tactile pressure measurement

The ability to measure human hand motions and interaction forces is critical to improving our understanding of manual gesturing and grasp mechanics. This knowledge serves as a basis for developing better tools for human skill training and rehabilitation, exploring more effective methods of designing and controlling robotic hands, and creating more sophisticated human-computer interaction devices which use complex hand motions as control inputs. This paper presents work on the design, fabrication, and experimental validation of a soft sensor-embedded glove which measures both hand motion and contact pressures during human gesturing and manipulation tasks. We design an array of liquid-metal embedded elastomer sensors to measure up to hundreds of Newtons of interaction forces across the human palm during manipulation tasks and to measure skin strains across phalangeal and carpal joints for joint motion tracking. The elastomeric sensors provide the mechanical compliance necessary to accommodate anatomical variations and permit a normal range of hand motion. We explore methods of assembling this soft sensor glove from modular, individually fabricated pressure and strain sensors and develop design guidelines for their mechanical integration. Experimental validation of a soft finger glove prototype demonstrates the sensitivity range of the designed sensors and the mechanical robustness of the proposed assembly method, and provides a basis for the production of a complete soft sensor glove from inexpensive modular sensor components.

Enhanced fabrication and characterization of gecko-inspired mushroom-tipped microfiber adhesives

Geckos exhibit a unique ability to adhere repeatedly and reversibly to a variety of surfaces. Considerable scientific and engineering efforts over the last decade have produced gecko-inspired adhesives which can outperform the gecko in some regards. However, the best results come from adhesives which are difficult to mass-produce, or degrade through repeated use. Here, we propose a method for fabricating micrometer-scale, gecko-inspired adhesive structures with mushroom tips in densely packed arrays using deep reactive ion etching (DRIE) and soft mold replication. We use xenon difluoride etching to release the cured polymer structures from the DRIE-processed silicon wafer, and soft mold replication to avoid surface fluorination in the final adhesive patches. The patterned adhesives exhibit more than an order of magnitude increase in pull-off force compared to an unstructured, flat control sample. More importantly, the adhesives’ structures retain 80% of their original attachment strength through repeated use, even after 1000 contact cycles. To investigate the importance of three parameters described in theoretical works, we characterize the effect of boundary conditions on friction, the effect of backing layer on pull-off force, and the effect of retraction speed on pull-off force. Our fabrication approach could be used to mass produce wafer-size patches of structured adhesive that exhibit higher repeatability and the utilized experimental adhesive characterization methods will allow better optimization of future gecko-inspired adhesive designs.

Directly Fabricating Soft Robotic Actuators With an Open-Source 3-D Printer

3-D printing silicone has been a long sought for goal by roboticists. Fused deposition manufacturing (FDM) is a readily accessible and simple 3-D printing scheme that could hold the key to printing silicone. This study details an approach to 3-D print silicone elastomer through use of a thickening additive and heat curing techniques. We fabricated an identical control actuator using molding and 3-D printing techniques for comparison. By comparing the free space elongation and fixed length force of both actuators, we were able to evaluate the quality of the print. We observed that the 3-D printed linear actuator was able to perform similarly to the molded actuator, with an average error of 5.08% in actuator response, establishing the feasibility of such a system. We envision that further development of this system would contribute to the way soft robotic systems are fabricated.

Adhesion recovery and passive peeling in a wall climbing robot using adhesives

This paper presents analysis and results for a small and agile wall climbing robots ability to regain lost adhesion due to degradation of dry fibrillar adhesives. To regain the lost adhesion, two feet are set to the surface and the robot performs a rocking motion on the side where the adhesion has dropped below a safety threshold. The rocking motion applies normal forces to preload the front and rear feet without letting the other foot detach from the surface by alternating the direction of the motor and only allowing small rotation of the leg. Experimental results show that the rocking motion is successful in regaining lost adhesion while using dry fibrillar adhesives on a smooth, vertical acrylic surface. The performance of the fibers over time limits the adhesion that can possibly be mechanically regained and as a result the fibers are over-designed, which gives rise to the need for a power efficient peeling mechanism. The peeling mechanism uses a conditionally locked ankle, implemented with magnets, and a slot to allow the axle to change a pulling force normal to the surface to be a pulling force perpendicular to the surface, which peels the fibers using the uneven loading. Experimental results illustrate that a passive peeling mechanism is successful in reducing the required power to peel. The presented advancements can be applied to other climbing robots using adhesives to allow for safer, more efficient climbing.

Development of the Polipo Pressure Sensing System for Dynamic Space-Suited Motion

Working inside the space suit causes injury and discomfort, but suit assessment techniques such as measuring joint torques and ranges of motion fail to evaluate injury because they fail to distinguish interactions between the human and the space suit. Contact pressure sensing would allow a quantitative assessment of the nature and location of suit-body contact where injuries occur. However, commercially available systems are not well suited for measurement inside the confined environment of the space suit during movement. We report on the design of a wearable pressure sensing system, the Polipo. The Polipo dynamically measures between 5 and 60 kPa of pressure with ~1 kPa sensitivity, is within 10% root mean square error from a known loading profile during dynamic movement, and is a standalone system able to accommodate a 50th percentile female to a 95th percentile male upper body dimensions with near shirt-sleeve mobility. This paper focuses on the upper body, but the methods may be extended to the full body as future work. It provides a pressure sensing system that could be applied beyond the field of aerospace to assess human-garment interactions, for example recommending armor protection for defense applications or to alleviate fall impacts for medical applications.