MIT
MIT Fluidic Sensor
MIT researchers have developed a method for 3D printing materials with tunable mechanical properties that sense how they are moving and interacting with the environment. The sensing structures are created using just one material and a single run on a 3D printer.
This was accomplished by beginning with a 3D printed lattice material and incorporating networks of air-filled channels into structure during the printing process. By measuring how the pressure changes within these channels when the structure is squeezed, bent or stretched, engineers can receive feedback on how the material is moving.
The method opens opportunities for embedding sensors within architected materials, a class of materials whose mechanical properties are programmed through form and composition.
Mechanical properties, such as stiffness or toughness, are altered in architected materials when controlling the geometry of its features. For example, in cellular structures like the lattices printed by the MIT researchers, a denser network of cells makes a stiffer structure.
MIT say that this technique could one day be used to create robots that are soft and flexible, with embedded sensors that enable the robots to understand their posture and movements.
Another possibility of this method is wearable smart devices that provide feedback on how a person is moving or interacting with their environment. You may think this technology sounds like something out of a sci-fi film, but it is now a realistic possibility.
“The idea with this work is that we can take any material that can be 3D printed and have a simple way to route channels throughout it so we can get sensorisation with structure. And if you use really complex materials, then you have motion, perception, and structure all in one,” said co-lead author Lillian Chin, a graduate student in the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL).
Joining Chin on the paper is co-lead author Ryan Truby, a former CSAIL postdoc who is now an assistant professor at Northwestern University; Annan Zhang, a CASIL graduate student; and senior author Daniela Rus, the Andrew and Erna Viterbi Professor of Electrical Engineering and Computer Science and director of CSAIL.
While architected materials can exhibit unique properties, integrating sensors within them is challenging given the materials’ often sparse, complex shapes. Placing sensors on the outside of the material is typically a simpler strategy than embedding sensors within the material.
However, when sensors are on the outside of the material, the feedback provided may not provide a complete description of how the material is deforming or moving.
3D printing was used to incorporate air-filled channels directly into the struts that for the lattice. This is how engineers receive feedback when the structure is squeezed or moved, as the channels deform and the volume of air changes. The corresponding change in pressure is measured with an off-the-shelf pressure sensor, which gives feedback on how the material is deforming.
As the “fluidic sensors” are incorporated into the material, they offer advantages over conventional sensor materials.
MIT
MIT Fluidic Sensor
The method used is digital light processing 3D printing. This process was used to create several of the lattice structures and demonstrated how the air-filled channels generated clear feedback when the structures were squeezed and bent.
“Importantly, we only use one material to 3D print our sensorised structures, We bypass the limitations of other multi-material 3D printing and fabrication methods that are typically considered for patterning similar materials,” said Truby.
The team 3D printed an HSA (handed shearing auxetics) soft robot capable of several movements, including bending, twisting and elongating. The robot was ran through a series of movements for more than 18 hours and used the sensor data to train a neural network that could accurately predict the robot’s motion.
Chin was impressed by the results. The fluidic sensors were so accurate that she had difficulty distinguishing between the signals the researchers sent to the motors and the data that came back from the sensors.
Chin said: “Materials scientists have been working hard to optimise architected materials for functionality. This seems like a simple, yet really powerful idea to connect what those researchers have been doing with this realm of perception. As soon as we add sending, then roboticists like me can come in and use this as an active material, not just a passive one.”
Rus added: “Sensorising soft robots with continuous skin-like sensors has been an open challenge in the field. This new method provides accurate proprioceptive capabilities for soft robots and opens the door for exploring the world through touch.”
“The use of additive manufacturing for directly building robots is attractive. It allows for the complexity I believe is required for generally adaptive systems,” said Robert Sheffield, associate professor at the Sibley School of Mechanical and Aerospace Engineering at Cornell University, who was not involved in this project.
He continued: “By using the same 3D printing process to build the form, mechanism and sensing arrays, their process will significantly contribute to researchers aiming to build complex robots simply.”
This research was supported, in part, by the National Science Foundation, the Schmidt Science Fellows Program in partnership with the Rhodes Trust, an NSF Graduate Fellowship, and the Fannie and John Hertz Foundation.
MIT has been home to multiple 3D printing developments in recent weeks, with a team of researchers developing 3D printed sensors for satellites, and others at the institution using artificial intelligence to correct additive manufacturing errors in real time.
