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Creating a robot that perfectly mimics the natural hand gestures of humans has perplexed researchers for years. How does one develop a robot that can not only pick up a cup of water, but also hold it at the correct angle so that it doesn’t spill on the floor? How about walking up stairs and sensing where every step is?
A new project at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), led by director Daniela Rus, is attempting to solve the gripping issue. The team created bendable and stretchable robotic fingers made out of silicone rubber that can lift and handle objects as thin as a piece of paper and as delicate as an egg.
Unlike robots with rigid, metal fingers, the soft silicone fingers don’t need to be given specific instructions about how to grasp varying objects. “Soft robotics” allow for less precision when picking up items.
“If you use rigid limbs, you have to be super precise and make sure you have fully defined contact when you pick something up or when you manipulate it,” explains PhD candidate Robert Katzschmann, who worked on the project and co-wrote the paper with Rus, graduate student Bianca Homberg, and postdoc Mehmet Dogar. The paper and research was presented last fall at the International Conference on Intelligent Robots and Systems.
The researchers’ tentacle-style gripper design expands to accommodate an object and grasps radially; however, it has one additional feature that allows it to accurately pick up objects: sensors. The robotic hand’s three fingers each have special sensors that can estimate the size and shape of an object precisely enough to identify it from a set of several items.
Why Soft Robotics?
The silicone fingers are actually part of a larger area of study out of Rus’ Distributed Robotics Lab at CSAIL, with the aim of showcasing the benefits of soft robotics made out of less conventional materials. For example, in 2014 another graduate student demonstrated a squishy snake-like robot which can navigate through tricky mazes.
Due to the soft materials used, these robots can not only squeeze into tight spaces, but also recover more easily from collisions and pick up and handle irregularly-shaped objects. However, because of soft robots’ flexibility, they often struggle with correctly measuring where an object is, or whether they actually picked the object up.
That problem is exactly why Rus and her team incorporated “bend sensors” into the silicone fingers so that they can send back information on the location and curvature of the object being grasped. Then, the robot can pick up an unfamiliar object and use the data to compare to already existing clusters of data points from past objects.
“By embedding flexible bend sensors into each finger, we got an idea of how much the finger bends, and we can close the loop from how much pressure we apply,” says Katzschmann. “In our case, we were using a piston based closed pneumatic system.”
Currently, the robot can acquire three data points from a single grasp, meaning the robot’s algorithms can distinguish between objects which are very similar in size. The researchers hope that further advances in sensors will someday enable the system to distinguish between dozens of diverse objects.
“I could potentially see the robots on the factory floor, mostly for low batch applications, where you can give the factory the ability for less computation and less adjustment,” remarks Katzschmann. “It might not be as quick as a specialized gripper, but for smaller batches you don’t really require that.”
Design & Development
When it’s attached to Rethink Robotics’ Baxter robot, the gripper far outperforms Baxter’s standard gripper, which couldn’t pick up a piece of paper or a CD. In fact, the default gripper often could not handle hollow objects like aluminum cans, crushing them instead.
The new robotic hand is further set apart by its ability to perform both a “pinch grasp,” where the object is held by the tip of the fingers, and an “enveloping grasp,” where the object is contained completely within the gripper.
Silicone rubber was chosen for the fingers for several reasons, but especially for its mechanical characteristics. The material is relatively stiff, yet flexible enough to bend easily with the pressure available from the gripper’s actuator pistons. In addition, the gripper’s interface and exterior finger-molds are 3D-printed, enabling the system to work on almost any platform.
“The reason why we’ve been using silicone rubber for these hands is it’s easily available as a two-part solution which you can mix together, and it cures in a few hours or even minutes depending upon what mix you use,” explains Katzschmann.
The major characteristic Rus and her team were evaluating in a material was its elongation-to-break. “You want them to undergo a lot of cycling with a lot of elongation force in the pleats of the fingers,” adds Katzschmann. “Each finger pleat has two thin skins on both sides, and they bubble up a little bit, which is stressful.”
The team had plenty of experience creating molds using silicone rubber from past projects in the Distributed Robotics Lab. The real challenge was finding the right sensors that would work within the system, and then running various experiments to fine tune some of the parameters.
The Next Generation
Almost immediately after submitting the paper for the gripper’s first design, the researchers began developing a second generation design. The paper detailing the new gripper was submitted for review in January, and the process will take roughly six months.
“With the newer model we’re working on, we have resistance sensors, but we’re also using force sensors,” says Katzschmann. “They’re very similar, but instead of just being sensitive to resistance change, they change their value based on the compacting of the sensor.”
In addition, the second generation gripper has four digits instead of three, which allows it to pick up even more objects.
“The challenging part is to pick up small objects that lay flat on the table, so we have to slide them to the table’s edge and then pick them up,” explains Katzschmann. “And if you don’t have a good vision system, and we didn’t initially do anything with vision for this project, then you’ll have a hard time doing fine positioning with small objects.”
Rus and her lab will continue to explore the potential of soft robotics, and how many existing robotic systems could benefit from adding a few soft elements. For example, when large, rigid robots fall down, the impact is rather traumatic. Adding a soft component to the contact point or within the actual joint of the robot could prove incredibly useful.
“The best part of these soft grippers is that they give you the flexibility to quickly change the kind of object you would like to pick up without worrying whether the gripper can deal with it,” muses Katzschmann. “I think the future of these systems will go into a direction of combining these fully soft fingers with skeleton structures.”
This article originally appeared in the April 2016 print issue of Product Design & Development.
