Soft robots can be incredibly robust and safe but typically fail to match the strength and precision of rigid robots. This dichotomy between soft and rigid is recently starting to break down, with emerging research interest in hybrid soft-rigid robots. In this work, we draw inspiration from Nature, which achieves the best of both worlds by coupling soft and rigid tissues—like muscle and bone—to produce biological systems capable of both robustness and strength. We present foundational, general-purpose pipelines to simulate and fabricate cable-driven soft-rigid robots with embedded skeletons. We show that robots built using these methods can fluidly mimic biological systems while achieving greater force output and external load resistance than purely soft robots. Finally, we show how our simulation and fabrication pipelines can be leveraged to create more complex robots and do model- based control.
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null (Ed.)The brushing of hair requires a complex un- derstanding of the interaction between soft hair fibers and the soft brushing device. It is also reliant on having both visual and tactile information. Guided by a recently developed model of soft tangled fiber bundles, we develop a method for optimizing hair brushing by robots which seeks to minimize pain and avoid the build up of jammed entanglements. Using an experimental setup with a custom force measuring sensor and a soft brush end effector, we perform closed-loop experiments on hair brushing of different curliness. This utilizes computer vision to assess the curliness of the hair, after which the hair is brushed using a closed loop controller. To demonstrate this approach hair brushing experiments have been performed on a wide variety of wigs with amount of curl. In addition to hair brushing the insight provided by this model driven approach could be applied to brushing of fibers for textiles, or animal fibers.more » « less
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One of the key challenges in soft robotics is the development of actuators which are truly soft and compliant, and can be adapted and tailored for different applications. In particular, the development of untethered soft actuators could enable robots to autonomously explore the world in an unrestricted manner, exploiting their compliant behavior. In this paper we present a method for creating fully soft, degradable actuators where the actuation of the system is controlled by setting physical parameters which ‘mechanically program’ the actuator determining the characteristics of the actuator. The actuation process is driven by the release of gas from a reaction between a bio-compatible acid and base. This approach allows for the creation of fully untethered actuators which could be deployed for use in agriculture, to make ingestible robots or to allow untethered exploration. This paper provides the ‘recipes’ for the development of the actuators used, and the methods for mechanically programming of the actuators.more » « less
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The development of compliant robotic manipulators which can show length change, compliance and dexterity could assist many challenging applications. Potential applications range from dexterous manipulation, robotic surgery or exploration of challenging environments. Despite significant developments in both fabrication and control approaches for continuum body manipulators, there have been few demonstrations of continuum body systems which display all these properties. We present a method for fabricating a continuum manipulation which shows extension, high force movements and a range of dexterous position. This approach uses 3D printing to create a flexible rack and pinion system. These high torque mechanisms are mounted at points along the 3D printed tracks to allow complex shape control of the continuum system. A controller has been also been developed based on a Piecewise Constant Curvature approximation to allow the position of the tip of the manipulator to be controlled, and motion paths to be followed. In this work, we show the force capabilities of this manipulator and demonstrate how multiple segments can be created for more complex movements.more » « less
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Wearable devices have many applications ranging from health analytics to virtual and mixed reality interaction, to industrial training. For wearable devices to be practical, they must be responsive, deformable to fit the wearer, and robust to the user's range of motion. Signals produced by the wearable must also be informative enough to infer the precise physical state or activity of the user. Herein, a fully soft, wearable glove is developed, which is capable of real‐time hand pose reconstruction, environment sensing, and task classification. The design is easy to fabricate using low cost, commercial off‐the‐shelf items in a manner that is amenable to automated manufacturing. To realize such capabilities, resisitive and fluidic sensing technologies with machine learning neural architectures are merged. The glove is formed from a conductive knit which is strain sensitive, providing information through a network of resistance measurements. Fluidic sensing captured via pressure changes in fibrous sewn‐in flexible tubes, measuring interactions with the environment. The system can reconstruct user hand pose and identify sensory inputs such as holding force, object temperature, conductability, material stiffness, and user heart rate, all with high accuracy. The ability to identify complex environmentally dependent tasks, including held object identification and handwriting recognition is demonstrated.
