Improving The Grip Of A Robot Arm

The robot arm was a pioneering design in automation. First developed and used in the middle of the last century, they fueled a manufacturing boom. Those early robot arms mainly completed tough, repetitive, and potentially dangerous tasks, like welding and hoisting, at speeds that revolutionized automation.

 

Their capabilities made them standard equipment in all manner of heavy manufacturing facilities. Through the 70s, 80s, 90s, and beyond, robotics engineers continued to advance early robotic arm designs, which broadened their applications.

Improved agility, control, and programmability brought robot arms into operating rooms as surgical robots, to critical situations as bomb disposal equipment, and in cleanrooms for the assembly of complex and delicate electronic components.

A robot arm’s ability to grip with the right combination of security and dexterity is a major defining feature of what it can accomplish. Designers and engineers are constantly working to refine the end-of-arm tooling (EOAT) element on robot arms. Also called the “end effector” this device will determine the purpose of a robot arm, in other words, what it can do and how.

EOAT might include very specific tools, such as a welder, airbrush, laser, or surgical scalpel, but more often, the robot claw or gripper has become a standard EOAT.

What Are Robot Grippers And What Can They Do?

Robot grippers include jaws, claws, and other parts that enable a robot to grasp, hold, and generally manipulate an object. EOAT parts that accomplish this with pressure, such as a suction plate or vacuum tube, or magnetic, electroadhesion, etc. are also sometimes referred to as grippers.

Credit: Ra Boe

They are categorized into four unique types: impactive, ingressive, astrictive, and contigutive. Impactive grippers include jaws, claws, and fingers. Ingressive grippers make use of penetrative elements like pins or hackles. Astrictive grippers apply a force that attracts and holds an object, such as electrostatic or magnetism.

Contigutive grippers work through direct contact and adhesion, whether accomplished through surface tension or an adhesive substance. Specific grippers provide unique benefits based on the type of objects that must be handled and the tasks that need to be performed. The operational environment and circumstances also factor in.

For example, cleanroom robots that handle extremely delicate and sensitive materials, like silicon wafers and photovoltaic cells, complete handling through the contactless manipulation of airflow. Robots used in food handling situations may use grippers with cryogenic capabilities, which rapidly freeze a small amount of liquid to briefly lift and move an item.

In the case of robots that interact directly with humans as cobots, many have impactive grippers that function like a human hand. This not only allows for the manipulation of a range of objects, it can promote a more collaborative and intuitive relationship between humans and machines.

Credit: Yingz

One of the challenges in developing an impactive gripper mechanism is achieving suitable force closure for a specific task—whether it’s sealing a shipping envelope, retrieving a heavy part from an inventory bin, or placing a delicate part in a human hand. Achieving these capabilities call for the right pairing of object recognition and manipulation.

How To Design A Better Robotic Claw

Robotic engineers have made monumental strides in the dexterity and capabilities of robotic claws and grippers. In addition to control, speed, and precision, object manipulation is now impressively fluid. Researchers and engineers have created remarkable prototypes that can quickly peel fruit or lift egg yolks without breaking them.

Robot grippers can now automatically adjust grip strength based on an object’s density and texture. Others can navigate complex environments while handling fragile and heavy items with appropriate levels of force. These abilities require highly sophisticated machine learning and AI capabilities that enable a robot to recognize an object and handle it based on a myriad of variables. But even with these advances, it always takes the right gripper to do the job.

Article Sources: 

https://www.theverge.com
https://www.therobotreport.com
https://news.mit.edu
https://www.digitaltrends.com
https://news.ncsu.edu

 

 

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