- This robot at the Georgia Institute of Technology is successfully sliding hospital gowns on people's arms. The machine is a PR2, and it taught itself to do this task in one day, by analyzing 11,000 simulated examples of a robot putting a gown onto a human arm. Some of its attempts were flawless, while others were complete failures. A problem the students encountered was that the simulated robot applied dangerous forces to the arm when the cloth would catch on the person's hand or elbow. From its mistakes, the PR2's neural network learned to estimate the forces applied to the human. In a sense, the simulations allowed the robot to learn what it feels like to be the human receiving assistance. Zackory Erickson, who is the Lead Georgia Tech Ph.D. student on the research team said, ""Doing thousands of trials on a human would have been dangerous, let alone impossibly tedious. But in just one day, using simulations, the robot learned what a person may physically feel while getting dressed." The robot also learned to predict the consequences of moving the gown in different ways. Some motions made the gown taut, pulling hard against the person's body. Other movements slid the gown smoothly along the person's arm. The robot uses these predictions to select motions that comfortably dress the arm.
Why it was created
- Over 1 million people in America require daily physical assistance to get dressed for the day. This is generally because of injuries, diseases, and old age. Creating a robot to help people with this daily task will affect the lives of millions of people, and could have a large impact on the world. By predicting the physical implications of their actions, robots can provide assistance that is safer, more comfortable and more effective.
How it works
- The machine doesn't use its eyes as it pulls the cloth. Instead, it relies on the forces it feels as it guides the garment onto a person's hand, around the elbow, and onto the shoulder. The PR2 estimates the forces applied to the human and predicts the consequences of moving the gown in different ways. The researchers varied the robot's timing and allowed it to think as much as a fifth of a second into the future while strategizing about its next move. The entire process takes about 10 seconds.
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