AI News, Inexpensive, Durable Plastic Hands Let Robots Get a Grip
Inexpensive, Durable Plastic Hands Let Robots Get a Grip
The human hand is one of nature’s marvels—and a stupendous challenge to engineers who would replicateit.
It’s an intricate assemblage with 29 flexible joints and thousands of specialized nerve endings, overseen by a control system so sensitive that it can instantly indicate how hot an object is, how smooth its surface is, and even how firmly it should be grasped.
But these generally employ simple parallel-jaw grippers that open and close on command to grasp, hold, or move a single type of object that they’ve been specifically programmed to handle.
That inflexibility isn’t a problem on the assembly line, but it won’t suffice for future robots designed to interact with people in a much less structured environment.
For example, opening a jar will require a robot to identify the size and shape of the object, grasp it effectively on the first try, and then apply enoughpressure and torque to open it—but not enough pressure to break it.
The quest for a versatile robot hand has produced designs that precisely mimic the human hand and others that look more like metal clamps.
The hands we’ve developed don’t look human, but they have proved adept at gripping and manipulating a wide variety of objects in many different settings and tasks.
Inspired by the success of the agency’s Grand Challenge, which helped to spur innovation in the field of self-driving cars, DARPA asked teams to develop multifingered robotic hands that could complete a variety of tasks, like picking up a telephone handset or operating a power drill.
Since the 1980s, researchers have been able to produce robotic hands with three or four fingers and an opposable thumb, replicating the structure of the human hand.
We dubbed our entry the iHY (pronounced “eye-high”) hand, representing the three organizations involved in developing it: iRobot, based in Bedford, Mass., which oversaw the project as a whole, and Harvard and Yale universities, whose students and professors brought additional years of expertise in underactuated hand design.
Each digit of the iHY hand consisted of two links—a proximal link that connected the finger to the base of the hand and a distal link that extended to the fingertip.
Those links were connected by a heavy-duty elastic joint that made the finger unit flexible, letting it bend on contact to match the shape of an object and form a grip around it, a technique known as passive adaptation.
And because the initial grip was passive, nothing had to run in reverse to loosen it—letting the tendons go slack released our hand’s grasp as its rubbery joints moved back into place on their own.
That was a level of control not available in the two other fingers, where a single tendon was connected to a single motor, allowing the digit to apply pressure and form a tight grip around objects.
To complete tasks like that, we used the wrap grasp, which let us lift and swing a hammer five times during the competition, taking an average of less than 15 seconds per swing.
The fiber-optic cables emitted light that hit the receptors differently depending on how the joint was bent—for instance, when the joint was bent at a 60 degree angle, the fiber-optic light hit the receptors in a different place and with a different intensity than at a 75 degree angle.
This controller acted as a sort of traffic cop for the whole hand, sending readings from the hand to the control computer via Ethernet and relaying commands from that computer to individual fingers.
Then we placed the printed-circuit boards and pressure sensors of the fingers in a pair of molds and poured rubber over these components, creating soft pads for the fingers that housed the more fragile electronics.
We affixed these pieces to the rubber finger pads and placed them in a final mold, where the upper and lower pieces that would make up the finger were chemically bonded to the rubber joint.
That helped us stay close to DARPA’s expectation that competitors produce a versatile robotic hand for around US $5,000—a fraction of the cost of models with comparable capabilities currently on the market.
The challenge, which took place in Arlington, Va., consisted of 19 tests—nine different objects the hand would have to grasp, nine it would have to grasp and then manipulate, and one test of the hand’s pure strength—each performed five times to demonstrate that no performance was a fluke.
In one impromptu test, an iRobot staffer placed a pair of tweezers and a thin straw on the test table, challenging us to pick up thetweezers with the iHY hand—and then pick up the straw using the tweezers.
Attached to humanoid robot bodies like that of Boston Dynamics’ Atlas, the iHY hand has been used in that competition to open doors and handle fire hoses, suggesting crisis response as one possible application for the iHY hand and itsdescendants.
While there are many fine robot hands available, the expense of procuring one—and of repairing one if it is damaged during an experiment—canmake researchers timid about how they use it, slowing the pace of research.
And with a strong, capable hand easily accessible, other teams can concentrate their efforts on writing new control software or making iterative improvements to the hardware, rather than building new hands from scratch.
As we develop the technology further, it’s likely that the company will offer several different models of the hand to research teams, from basic, stripped-down versions to more complex models with full sensor suites.
By making the technology easily accessible to other teams of researchers and engineers, we think those improvements will come more quickly, not just to the hands we’ve worked on but to the field of robotic manipulation as a whole.
While advances in rapid-prototyping have made it increasingly tractable to make custom parts expediently and on-demand, design choices must be made to make robotic hands suitable for repeated functional use, not just design prototyping.
Underactuated hands have been shown to improve the generality of simple grippers by adaptively conforming to the surface of objects without the explicit need for sensors or complicated feedback systems.
- On Thursday, March 21, 2019
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