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Intel Develops $50 3D Printed OpenBot to Advance Robotics Accessibility

Researchers at Intel Labs have developed a smart robot that anyone with a smartphone can build, using open source code, a 3D printer, and $50. What is different with this 3D printed robot is that the smartphone isn’t just used to control the robot, as with devices such as MobBob or Qualcomms Micro Rover, but is used directly as the ‘brains’ of the bot, leveraging the advanced features and operating systems in today’s smartphones to enable high-quality sensing and computation, while improving affordability, accessibility and scalability—all within a $50 budget (not including the smartphone).

While there have been efforts previously at making robot technology affordable and scalable, compromises have been made either in design, functionality, or performance. Relatively expensive robots in this area of research can cost between $2,000-$5,000, while mobile-based robots are significantly less expensive, yet still fall between $250-500 in cost, such as the AWS DeepRacer, DJI Robomaster S1, Nvidia JetBot, and DukieBot.

As the study says, “the aforementioned projects use the smartphone as a remote control for teleoperation, offload data to a server for processing, or rely on commercial or outdated hardware and software. In contrast, our platform turns a smartphone into the brain of a fully autonomous robot with onboard sensing and computation.”

With this approach, Intel researchers have leveraged the advantages of today’s smartphones to enable navigation and real-time sensing and computation for a wheeled robot body that costs less than $50. The features of smartphones that make this possible include advanced imaging technology, processing power, navigation, connectivity, sensors, AI accelerators for neural network inference, rapidly upgraded and evolving software and hardware ecosystems. In turn, the ‘OpenBot’ is capable of advanced applications such as person following and autonomous navigation.

While a large part of the cost, about 40%, is that of the batteries, the price can be further reduced by scaling production, as more units are made. The top plate with the phone mount and the bottom cover, weighing 146g and 103g respectively, are 3D printed in PLA and take about 23 hours in total to 3D print using an Ultimaker.

Image Courtesy of Intel Labs

The Android application allows for connectivity, processing and audiovisual sensory inputs (camera, gyroscope, accelerometer, magnetometer, ambient light sensor, barometer). Common game controllers can be connected via Bluetooth to remotely operate the OpenBot. The learning-based algorithms, unlike classic motion planning algorithms, uses neural network processing to detect objects or people, and navigate autonomously.

OpenBot smartphone-based system Image Courtesy of Intel Labs

Explaining the difference it makes in using an widely available, constantly upgraded, open-platform such as Android, as opposed to specific custom software solutions, the study states,

“In contrast to other robots, our platform has an abundance of processing power, communication interfaces, and sensors provided by the smartphone. Existing robots often rely on custom software ecosystems, which require dedicated lab personnel who maintain the code, implement new features, and implement drivers for new sensors. In contrast, we use Android, one of the largest constantly evolving software ecosystems. All the low-level software for sensor integration and processing already exists and improves without any additional effort by the robotics community. All sensors are already synchronized on the same clock, obviating what is now a major challenge for many existing robots.”

Comparison of Wheeled-robotics solutions Image Courtesy of Intel Labs

The advantages of this approach to improving the accessibility and scalability in robotics is more than obvious when comparing the features and specifications across wheeled-robotics platforms. With nearly all the features available, an open Android operating system, using any smartphone available today, not only to control, but to drive learning-based algorithms and AI-based applications in person following and autonomous navigation, and its cost-effectiveness, the OpenBot from Intel Labs is leaps and bounds ahead of any other low-cost robotic solution available publicly.

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Robotics Manufacturing at the Next Level with 4D Printed Soft Robotics

Authors Ali Zolfagharian, Akif Kaynak, and Abbas Kouzani explore the growing science of soft robotics, outlining their findings in the recently published ‘Closed-loop 4D-printed soft robots.’ Emphasizing how fast this field is growing, the authors make it clear that many different levels of research and development are involved, from materials and modeling to performance control and more. 3D printing allows for great customization but in taking the process to the next dimension with 4D printing, researchers can add much greater functionality to robotics.

Closed loop 4D printing allows researchers to enhance soft robots with sensors, actuators, and controls for better performance overall. The authors integrated such details into their electronic innovations here, using a data-driven, machine-learning model meant to handle a new hierarchy of tasks to include:

Grasping
Sorting
Climbing or crawling
Inspecting
Search and rescue
Drug delivery systems

“Origami-like soft robots can provide variable stiffness with higher efficiency and dexterity required in specific tasks, which conventional robots cannot handle,” stated the researchers. “Closed-loop 4D-printed soft robots may be also used in autonomous surgeries, laparoscopy, and endoscopy.”

Diagram of closed-loop 4D-printed soft robot.

Machine learning plays an obvious—and substantial—role in 4D printed soft robots, alleviating some of the challenges involved in ‘diverse manipulation tasks.’ Machine learning can be used to develop such robotics during the manufacturing process, and algorithms can be used to speed up property optimization like viscosity and orientation of parts.

“Through the integration of physical models, the ML uses sparse datasets in a statistical learning framework to predict materials and 3D printing processing parameters to increase 3D printing speed and fidelity,” stated the researchers.

With 3D printing, the following features can be introduced:

Targeted anisotropy
Variable stiffness
Spatially heterogeneous mechanical strengths

The use of machine learning is advantageous for this area of robotics, offering increased dimension and more, with a variety of control mechanisms available: open-loop controllers, closed-loop (with embedded soft sensors), and more.

“The mechanisms and materials used in the construction of soft robots are similar; hence, the control can be inspired by a learning strategy that deals with high nonlinearity and agility,” explain the researchers.

3D-printed sensors with applications in 4D-printed soft robots. (a) 3D-printed integrated strain sensor (reproduced with permission from Copernicus Publications on behalf of AMA [42]); (b) 3D-printed sEMG electrodes (reproduced with permission from Copernicus Publications on behalf of AMA [42]); (c) 3D-printed piezoelectric sensor in jellyfish soft robot (reproduced with permission from SPIE [67]); (d) 3D-printed e-tongue sensor (reproduced with permission from Frontiers [110]); (e) 3D-printed pressure sensors (reproduced with permission from John Willey and Sons [71]); (f) 3D-printed fluid flow rate sensor (reproduced with permission from IOP Publishing [98]). (g) 3D-printed dog nose for gas detection (reproduced with permission from Nature Publishing Group [109]); (h) 3D-printed flexible tactile sensor (reproduced with permission from Springer [58]); (i) 3D-printed thermochromic and solvatochromic sensors (reproduced with permission from John Wiley and Sons [100]).

Just 3D printed sensors alone are now advanced enough to be printed in spatial levels, and with 4D printed robotics, such features can be ‘categorized and introduced.’ There is also the possibility for the potential of amphibian soft robots able to perform a wide range of tasks.

“Despite existing problems, 4D-printed soft robots are achievable through the integration of 3D-printed soft sensors and actuators with machine learning algorithms and FEM,” concluded the researchers. “Integrated 3D-printed actuators and sensors are feasible but limited by the nature of materials utilized. The future of enhancing closed-loop 4D-printed soft robots accordingly relies on integration of suitable materials, machine learning approaches and control algorithms.”

Soft robotics continue to be increased subject of research, from new designs and frameworks to continued customizations and different materials. What do you think of this news? Let us know your thoughts; join the discussion of this and other 3D printing topics at 3DPrintBoard.com.

Integrated 3D-printed soft sensors and actuators: (a) 3D-printed embedded sensor in pneumatic soft actuator (reproduced with permission from SPIE [126]); (b) 3D-printed soft gripper with printed embedded sensors (reproduced with permission from John Wiley and Sons [9]); (c) 3D-printed tactile sensor on 3D-printed prosthetic hand (reproduced with permission from the American Chemical Society [34]); (d) 4D-printed multistable thermal actuator (reproduced with permission from John Wiley and Sons [150]); (e) Bistable 3D-printed soft actuator (reproduced with permission from MDPI [148]); (f) 3D-printed variable stiffness soft actuator with an integrated joule heating circuit (reproduced with permission from John Wiley and Sons [151]).

[Source / Images: ‘Closed-loop 4D-printed soft robots’]

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3D Printed Cellular Fingers Offer Material Balance Required for Modern Robotics

In ‘Toward a Smart Compliant Robotic Gripper Equipped with 3D-Designed Cellular Finger s,’ authors Manpreet Kaur and Woo Soo Kim delve into the world of combining 3D printing and robotics. Their recently published paper focuses on the design of a robotic structure with deformable cellular structures that are easy to fabricate.

The conventional metal robot or robotic components are increasingly being upstaged by softer materials that offer more versatility for industrial applications. Not only that, many of these new materials are able to morph to their environment, affected by environments such as temperature or moisture. Kaur and Kim remind us that many of these innovations are originally inspired by nature, such as the movement of and the frictional properties of the snake.

Design and fabrication of multi‐material auxetic structure: A) 2D sketch of the re‐entrant honeycomb unit cell with defined parameters. B) Schematic demonstration of filament extrusion–based multi‐material 3D printing. C) Different designs of auxetic unit cells with two important parameters, α (the ratio of length of vertical strut h by re‐entrant strut l) and θ (the re‐entrant angle), defined in the sketch (A). D) The CAD image of the 3D re‐entrant honeycomb structure made by joining two 2D structures at 90°. The single tone gray color indicates the usage of a single material that is a TPU‐based flexible material. E) A dual‐material‐based auxetic unit cell where the re‐entrant struts (red) made of flexible material and the vertical struts (gray) made of rigid material. F) Different designs of dual‐material‐based auxetic unit cell, where the joints (gray) are made of flexible material and the rest of the portion of the struts (blue) are printed with the combination of both flexible and rigid material with equal proportion.

In creating soft robotics, however, there is the challenge of finding a balance between flexibility and structural stiffness and incorporating electronics which usually consist of a variety of different bulky systems. The cellular finger noted in this research can be made with embedded sensors in the fingertips, allowing for a significant gripping force of 16N, and the ability to pick up numerous objects—and acting as an example of more complex architectures for better functionality and performance overall.

“Stretching‐dominated cellular solids, such as octet, octahedral, and so on, show higher initial yield strength compared with bending‐dominated foamed materials, which is due to their different layout of structural components and makes them better alternatives for lightweight structural applications. One such unique spatially arranged structure produces a negative Poisson’s ratio (NPR); these are called auxetics. Like other types of mechanical metamaterials, the NPR of auxetics is generally a direct consequence of the topology, where the joints rotate to move the structure,” state the researchers.

Characterization of 3D printed auxetic structures: A) Compressed samples from the design with α = 1.5 and θ = −20°. Three different material distributions in the unit cell (single, dual 1, and dual 2 designs) are studied. Images were captured for each sample at 0%, 20%, and 40% strains. B) Stress–strain graph of three samples with different combinations of α = 1.5, 2 and θ = −20°, −30 ° for designs (single, dual 1, and dual 2). The legends read as “a” for alpha, “t” for theta, and S, D1, D2 for single, dual 1, and dual 2, respectively. C) Finite element analysis (FEA) simulation analysis of compressed auxetic unit cell to study the different stress distributions in the elastic region for the three different designs. The color code is kept constant and is defined next to each image. The corresponding elastic curves from experiment and simulation are compared for each case. D) The cellular finger is designed using the rigid stretching‐dominated octet structure for the main body and using chosen auxetic structure (α = 1.5 and θ = −20°) with dual 2 designs for the joints.

NPR materials are also able to deform and show ‘compliant-bending behavior.’ In this research project, Kaur and Kim used honeycomb structures—again, inspired by nature—examining their ability to absorb energy and bend. These re-entrant structures are more easily translated to the 3D realm and allowed the authors to experiment regarding parameters and resulting cell properties. The end goal was to achieve deformity, along with suitable durability and energy efficiency.

With the use of porous cellular materials meant to meet the balance of both softness and flexibility and the need for firmness also, the researchers were able to roll their knowledge of materials, manufacturing, and robotics into one—along with 3D printing and the use of triple materials. The robotic gripper finger was made up of the following lightweight parts:

Three octet segments
Two auxetic joints (mimicking human bones and joints)
Integrated pressure sensor on the fingertip

The following materials were used for 3D printing the single, dual 1, and dual 2 designs: SemiFlex, PLA, and carbon fiber reinforced PLA (CFRPLA). The porosity level allowed for the sought-after balance in a lightweight structure as well as offering the proper rigidity for various gripping functions. The overall design was also responsible for the system of fingers able to deform as needed, in tune with objects and their specific shapes—while the fingertip sensors monitoring the environment.

Mechanical properties of the samples from compression test

“Our architectured robotic finger is a starting point of cellular design concept. Therefore, there is a lot of room for further research in this topic. Design of other mechanical metamaterials has lots of opportunities, so other lattice structures can be investigated to tune additional mechanical deformation functionality in the robotic finger,” concluded the researchers.

“The optimization of sensor design and addition of other sensors can also be investigated to achieve its ubiquitous performance. This compliant robotic design with metamaterial body can prove to enhance the functionality and durability of robotic bodies for prosthetic or industrial applications, thus developing new generation of robotic systems with better performance and greater adaptability in a variety of tasks.”

Robotics and 3D printing are paired up often these days, in projects ranging from uses in furniture manufacturin g to soft robotics, and more. What do you think of this news? Let us know your thoughts! Join the discussion of this and other 3D printing topics at 3DPrintBoard.com.

Auxetic unit cell designs based on different α and θ parameters

[Source / Images: ‘Toward a Smart Compliant Robotic Gripper Equipped with 3D-Designed Cellular Finger s’]

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MIT: Automated System Designs and 3D Prints Optimized Actuators and Displays to Spec

Actuators are complex devices that mechanically control robotic systems in response to electrical signals received. Depending on the specific application they’re used for, today’s robotic actuators have to be optimized for a variety of features, such as appearance, efficiency, flexibility, power consumption, and weight, and all of those parameters have to be manually calculated by researchers to find the right design; add 3D printing with multiple materials to make one product and things get even more complicated. This obviously leaves a lot of room open for human error.

But, a team of researchers from MIT – which knows a thing or two about 3D printing actuators – developed an automated system that can design and 3D print actuators that are optimized to many specifications. Basically, this system is completing a task that’s too complex for researchers to do the old school way.

“Our ultimate goal is to automatically find an optimal design for any problem, and then use the output of our optimized design to fabricate it. We go from selecting the printing materials, to finding the optimal design, to fabricating the final product in almost a completely automated way,” stated Subramanian Sundaram PhD ’18, a former graduate student in MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL).

Overview of the specification-driven 3D printing process. The structure of individual actuators (or the arrangement of multiple actuators) is optimized using a multiobjective topology optimization process. The optimization uses the bulk physical properties of the individual materials and the functional objectives as inputs. The generated optimized voxel-based representation of the structure is used by the printer to fabricate the optimized structure using a drop-on-demand inkjet printing process. A rigid acrylate polymer (RIG), an elastic acrylate polymer (ELA), and a magnetic nanoparticle (Fe3O4)/ polymer composite (MPC) are the materials used. The contrast in the optical, mechanical, and magnetic properties is used to simultaneously optimize the visual appearance and actuating forces while generating voxel-level design.

Sundaram is the first author of a paper, titled “Topology optimization and 3D printing of multimaterial magnetic actuators and displays,” that was published in Science Advances; additional authors are former MIT postdoc Melina Skouras; David S. Kim, a former researcher in the Computational Fabrication Group; Louise van den Heuvel ’14, SM ’16; and Wojciech Matusik, head of the Computational Fabrication Group and an MIT associate professor in electrical engineering and computer science.

To show how their system works, the researchers used it to make actuators that show two black-and-white images at different angles. When it’s flat, one actuator shows a Vincent van Gogh portrait, but tilted at an angle once it’s been activated, the image shifts to Edvard Munch’s famous painting “The Scream.” Another example they created are 3D printed floating water lilies, which feature petals that have actuator arrays and hinges that fold in response to magnetic fields that are run through conductive fluids.

When multiple materials are used to 3D print one product, the design’s dimensionality gets pretty high.

Sundaram explained, “What you’re left with is what’s called a ‘combinatorial explosion,’ where you essentially have so many combinations of materials and properties that you don’t have a chance to evaluate every combination to create an optimal structure.”

Three polymer materials were customized with the specific properties of color, magnetization, and rigidity that were needed to build the actuators, producing an opaque flexible material used as a hinge, a brown nanoparticle material that responds to a magnetic signal, and an almost transparent rigid material. Then, the characterization data is added into a property library, and the system draws from this to assign various materials to fill different voxels. Grayscale images, like the flat actuator which displays van Gogh’s portrait until it’s tilted into “The Scream,” are used as system input.

Panel optimization for both optical and mechanical properties, given a pair of target grayscale images.

Then, through a sort of trial and error process, 5.5 million voxels are “iteratively reconfigured” in a simulation to match a specific image and “meet a measured angle.” If the arrangement of voxels doesn’t portray the target images, both at an angle and straight on, an error signal tells the system which voxels are correct and which need to be changed. For example, if the brown magnetic voxels are shifted, removed, or added, the actuator’s angle will change when a magnetic field is applied, but how this alignment will affect the target image must also be taken into consideration.

A computer graphics technique called “ray-tracing,” which simulates the path of light interacting with objects, was used to compute the appearances of the actuators at each iteration. These simulated beams shine through the actuator at each voxel column, which can contain over 100 voxels. If an actuator is flat, the beam produces a dark tone by shining down on a column with lots of brown voxels. But when it’s tilted, misaligned voxels will be illuminated, and clear voxels may shift into the beam, while brown ones move away, so a lighter tone appears.

“We’re comparing what that [voxel column] looks like when it’s flat or when it’s titled, to match the target images. If not, you can swap, say, a clear voxel with a brown one. If that’s an improvement, we keep this new suggestion and make other changes over and over again,” explained Sundaram.

The MIT system uses ray-tracing to align both light and dark voxel columns in the appropriate spots for the flat and angled images. Eventually, after a few to dozens of hours and 100 million iterations, the correct placement of each material in each voxel is found to generate two images at two angles.

A custom 3D printer with drop-on-demand inkjet technology is used to make the actuator. Tubs of the different materials are connected to print heads with individually controlled nozzles, and the designated material is dropped, layer by layer, into each of the voxels.

According to Sundaram says their work could be a step in the right direction for designing large structures like airplane wings. Actuators that have been optimized for appearance and function could also be used for biomimicry in robotics.

Sundaram said, “You can imagine underwater robots having whole arrays of actuators coating the surface of their skins, which can be optimized for drag and turning efficiently, and so on.”

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[Source/Images: MIT]

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Purdue Researchers Create Soft Robotics Users Can Customize & Make Using 3D Printing

Researchers have patented promising new robotics technology created through the Purdue Office of Technology Commercialization, and outlined in ‘3D Architected Soft Machines with Topologically Encoded Motion.’ Authors Debkalpa Goswami, Shuai Liu, Aniket Pal, Lucas G. Silva, and Ramses V. Martinez have developed robotic devices that can be 3D printed and customized by users, depending on their needs.

This technology may both surprise and fascinate users, who in the past have expected robots to make things for them—but they may not have expected to be the ones creating the robots from home or the workshop. A 3D printed robot, while not completely able to protect users, can at least communicate with them, ask basic questions, and sense movement such as a fall, acting as a more complex panic button in these cases.

“Unfortunately, the external hard structure of current caregiving robots prevents them from a safe human-robot interaction, limiting their assistance to mere social interaction and not physical interaction,” said Ramses Martinez, assistant professor at the School of Industrial Engineering and in the Weldon School of Biomedical Engineering in Purdue’s College of Engineering. “After all, would you leave babies or physically or cognitively impaired old people in the hands of a robot?”

Purdue University researchers have developed a new design method to create soft robots (Artist rendering by Ramses Martinez)

Users can create their own CAD files, shaping the robot, and then designating what types of movements it will make. The researchers have created a customized algorithm that converts the data into a 3D architected soft machine (ASM). And indeed, this opens a brave new world to users everywhere as they can print the robots on virtually any 3D printer.

The fabricated ASMs can mimic human locomotion, operated with tiny motors that rely on nylon to pull the limbs back and forth. The researchers state that these customized robots and their soft materials can be stretched to beyond 900 percent of their initial length.

“ASMs can perform complex motions such as gripping or crawling with ease, and this work constitutes a step forward toward the development of autonomous and lightweight soft robots,” Martinez said. “The capability of ASMs to change their body configuration and gait to adapt to a wide variety of environments has the potential to not only improve caregiving but also disaster-response robotics.”

While users can 3D print customized robotics, the actual forms created move in the realm of the 4D, responding and morphing with their own environment. The researchers state that they can perform a wide range of motion, depending on need.

“The topological architecture of these low‐density soft robots confers them with the stiffness necessary to recover their original shape even after ultrahigh compression (400%) and extension (500%),” state the researchers in their paper. “ASMs expand the range of mechanical properties currently achievable by 3D printed or molded materials to enable the fabrication of soft machines with auxetic mechanical metamaterial properties.”

You don’t have to be an engineer or a techno-geek to understand that today (which used to be that distant, faraway future) has not yielded the type of progress we expected from robotics. And while we are not being served and accompanied 24/7 by charismatic androids, significant and interesting developments have certainly been achieved—from 3D printed robots that pick up trash for us, to construction robots—and even swarms of robots doing the 3D printing work for us. The picture may be different from what we imagined, but in the end—far more spectacular. Find out more about the recent research in soft robotics here, serving as part of the university’s Giant Leaps celebration in connection with their 150th anniversary.

Purdue researchers have developed a new design method that will enable anyone to quickly design and fabricate soft robots using a 3D printer (Photo credit: Purdue University)

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[Source / Images: Purdue University]

Embedded 3D Printing and Sensors Lead to Soft Robotic Fingers

Robotics and 3D printing have gone hand in hand for years, but researchers Ryan L. Truby, Robert K. Katzschmann, Jennifer A. Lewis, and Daniela Rus have put a much more literal touch on that in their study, ‘Soft Robotic Fingers with Embedded Ionogel Sensors and Discrete Actuation Modes for Somatosensitive Manipulation,’ outlining their latest innovations: grippers that are highly functional due to their adaptability for gripping.

Examples of manipulator poses. Photographs of the soft gripper during no (left), base-only (center), and full-finger actuation at inflation pressures of 140 kPa. Scale bar is 15 mm.

Rigid robots are obviously unwieldy for many applications. Up until now, however, it has still been difficult to design and manufacture soft actuators with the desired features, as they require extensive dexterity in action and a closed-loop control mechanism. Here, 3D printed embedding is the key to making soft robotic grippers shaped like hands, able to show us the future for such devices in applications like:

Automated assembly
Packaging
Prosthetics
Conservation
Extreme environments

Examples of object grasping. (a-b) Examples of grasping poses are shown for holding a toy strawberry (a) and pear (b) during base-only (left) and full-finger actuation (right). (c) Examples of objects that can be grasped by the soft gripper with appropriate pre-grasp orientation. Inflation pressure is 140 kPa in each photograph. Scale bars are 15 mm.

“However, creating soft robots with multi-degree-of-freedom (DOF) actuation and somatosensory capabilities remains a significant hurdle that limits their practical use in these areas,” state the researchers. “Most soft robotic manipulators operate via open-loop control and have simple, single-DOF actuation, such as uniform bending or twisting.”

“Given the simplicity of fluidic actuation and molding-based fabrication techniques, fluidic elastomer actuators (FEAs) are a popular platform for producing soft manipulators. Unfortunately, these techniques require multiple assembly steps, especially when multi-DOF actuators are desired.”

Soft robotic gripper with EMB3D printed soft fingers. (a) Three
fingers comprise a soft gripper fixed to a robot arm. (b) Inflating the tip (left), base (center), or tip and base (right) actuator networks enable three modes of finger bending and (c) different grasps. (d) Schematics of the finger from side (top), top-down (middle), and bottom-up (bottom) views. Scale bars are 30 mm.

The need for sensors often makes devices like this unlikely as greater complexity is added to the design and the actual manufacturing. For this study, and the integration of soft somatosensitive manipulation, the research team strategized on how to make actuators comprised of both discrete actuation modes and integrated sensors. Luckily, they were able to turn to 3D printing, a technology often quite appealing to persistent innovators who know ‘where there is a will there is a way.’

Each finger is made up of two ‘fluidic networks’ running throughout the artificial tip, base, and ‘full-finger actuation.’ There are a variety of different ways that the hand can grip, with four different sensors controlling each digit that contains an organic ionogel for sensory feedback.

“Fabricating FEA-based soft robots with integrated sensors and multi-DOF actuation requires many steps,” state the researchers. “Prior work has used molding techniques to make soft quadrupeds, swimming fish, tentacle-like actuators, and hand-like manipulators with several DOF.”

“By contrast, 3D printing offers a promising approach for rapidly designing and fabricating complex soft actuators. Several light and ink-based printing techniques have recently emerged for directly building multi-DOF soft fingers, legs, grippers, and integrated robotic systems.”

The FEAs may work in either a rigid or soft capacity, but the researchers point out that more traditional, less flexible sensors do not work with FEA soft elastomers. The rigid parts that are required for the elastomeric waveguides do not interface well either. The team goes on to point out also that liquid metal sensors are not a good choice due to the ‘potential displacement of their passivating oxide layers over time.’

As is so often the case in human creativity, science, and 3D design, nature is an enormous inspiration. For this study, the researchers drew on the natural sensory capabilities and dexterity of human hands, creating the three-fingered robotic gripper. Each one was 3D printed using EMB3D printing, which allows for arbitrary patterns to be created—and here, the design is modular. 3D printing took around 90 minutes, curing overnight, and then the parts were refrigerated for an hour to liquefy the ink. The soft fingers were wired together, and then inflated with a pneumatic valve.

“We are now actively pursuing new multi-DOF, sensorized soft actuator designs using these methods to create more complex types of dexterous, soft robotic manipulators,” concluded the researchers. “Soft manipulator designs that we are exploring have different finger numbers, orientations, designs, and sensing motifs than the gripper presented here. Working with established algorithms in grasp planning with soft grippers and object recognition, we aim to develop soft robots with advanced manipulation capabilities that will be useful in myriad applications.”

3D printing allows users (and researchers especially) much more latitude in the lab, and along with accompanying electronics and robotics applications, this often involves experimentation and innovation resulting in items like stretchable electronics, liquid applications, and integration within the internet of things. Find out more about the use of embedded 3D printing for robotics here. What do you think of this news? Let us know your thoughts! Join the discussion of this and other 3D printing topics at 3DPrintBoard.com.

Free and blocked displacement characterization of soft sensorized fingers. (a-c) Photographs of a soft finger in non-inflated (left) and various maximum inflation states for tip (center-left), base (center-right), and full (right) actuation modes during (a) free displacement and blocked displacement with the (b) short and (c) long mounts, whose edges are indicated by the red arrows. Scale bars represent 25 mm; g indicates acceleration due to gravity. (d-l) Resistance change, ∆RS, versus inflation pressure is provided during inflation-deflation cycles (indicated by filled/open circles, respectively) for
the long (SCurve,L) and short curvature (SCurve,S) and short (SContact,S) and long contact (SContact,L) sensors during (d-f) free displacement and blocked displacement with the (g-i) short and (j-l) long mounts. Plots correspond to ∆RS during (d, g, j) tip, (e, h, k) base, and (f, i, l) full-finger actuation. In (l), ∆RS for SContact,L is scaled by a factor of 0.2 (to idenically scale axes across subfigures). (n = 3, error envelopes represent standard deviation.)

[Source / Images: ‘Soft Robotic Fingers with Embedded Ionogel Sensors and Discrete Actuation Modes for Somatosensitive Manipulation’]

Soft Robotic Sheets Can Make Inanimate Objects Move

Among 3D printing’s many applications, the technology often crosses over into the field of robotics, including soft robotics. Soft robotics is a field that has been changing the way people look at robots, taking them from rigid metal creations to something much more fluid and flexible. Applications include synthetic muscle, prosthetics, search and rescue tools, and more. Now researchers at Yale University are creating soft robots from everyday objects.

The researchers created “skins” by embedding sensors and remotely operated actuators into elastic sheets. When those skins were wrapped around objects, the objects could move, grasp, and even walk. A stuffed horse was able to move its legs when wrapped with the sheets, and a foam tube was able to squirm. The research is described in a paper entitled “OmniSkins: Robotic skins that turn inanimate objects into multifunctional robots.“

Rebecca Kramer-Bottiglio, Assistant Professor of Mechanical Engineering and Materials Science and leader of the research, said that the sheets could be used to create improvised robots that could be used in disaster situations, for example.

“A designer could quickly construct a robot using the robotic skins wrapped around whatever deformable materials they have access to and stick a camera on it, and then deploy the robot for exploration of small or dangerous spaces,” she said. “Robotic skins can be applied to, removed from, and transferred between different objects, and used in combination to create many different configurations to perform many different tasks.”

Kramer-Bottiglio and her colleagues plan to use 3D printing to build additional components for testing the robotic sheets, as well as creating clay structures that can morph into different shapes.

“I’m really excited to see what other people will do with robotic skins,” Kramer-Bottiglio said. “The possibilities are endless.”

The field of soft robotics encompasses a wide variety of production techniques, although 3D printing has been one of the most common methods of fabricating them. Soft robotics has the potential to eliminate many components from traditional robots, doing away with circuits and other clunky parts in favor of actuation by light or chemical reaction. With this new way of looking at robots, they can be made and activated more easily, and used in situations that involve small or unknown spaces.

“This is a very exciting study that demonstrates the versatility and adaptability of soft robotics,” said Conor Walsh, an Associate Professor of Engineering and Applied Sciences at Harvard University. “The idea that we can have a soft and flexible sheet, wrap it around any surface, have it learn what it is attached to and then move it in some desired way has lot of potential.”

Soft robots can be made out any number of flexible materials, but the researchers’ idea is novel in that it can transform ordinary objects into robots just by wrapping them in fabric. As Kramer-Bottiglio pointed out, this means that in an emergency situation, any flexible item that happened to be at hand could be quickly turned into a search and rescue bot – or, in a less urgent situation, kids could turn their favorite stuffed animals into companions that could move around the house. Whether that’s fun or creepy is a matter of opinion, but it’s hard to argue against this new method of robot creation as being potentially very useful in the future.

Authors of the paper include Joran W. Booth, Dylan Shah, Jennifer C. Case, Edward L. White, Michelle C. Yuen, Olivier C. Choiniere and Rebecca Kramer-Bottiglio.

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