"The robots are not at the level of task autonomy we would like to see," said Pratt. "We expect their human operators will play a big role. Ultimately, the robot will need to recognize its environment and plan its moves to accomplish its tasks."
The point of the challenge is to push robotics technology to become more autonomous, deciding themselves how best to move around obstacles and how to get to where they need to be.
"It's a robot approximating human capabilities," said Connor. "This is the most ambitious challenge to get all of the systems integrated into a robot acting outdoors. Each individual piece, such as the steering controller or obstacle avoidance, has been demonstrated. But taking that obstacle detection capability into a humanoid robot that is actually steering a car? That's new."
Human controllers will be involved at a higher level than in the past.
For instance, the robots are too complex to control every joint so a human may have to command it to turn a valve while the device figures which individual joints, like the elbow and the wrist, need to be engaged.
"The software is interpreting these high-level commands into low-level commands for how it will get that done," noted Connor.
And R.J. Linton, a Ph.D. candidate and member of the team from the Worcester Polytechnic Institute, said it's a much greater challenge to build the software for a humanoid robot, than for a four-legged or wheeled robot.
"The human form is bad in general," he explained. "We have an unstable gate. The humanoid shape is inherently unstable. You're always shifting weight to maintain balance. You have to teach a robot how to do that. Atlas has to always be kind of moving, just like a human."
Neuhaus said humanoid robots are in their infancy and called the challenge a good starting point for needed research.
"There are some technical challenges -- no one really felt it was possible," he said. "It involves solving a lot of problems at the same time. You have to solve the [artificial intelligence] challenge, embedded computers, actuation, algorithms for walking and balancing and manipulation. You have to fit all of that into the same research project. Researchers might work on individual parts but not the entire thing."
A big issue for a humanoid robot, for instance, is enabling it to have the hands do something while it's walking. Those two simple sounding tasks might involve 30 or 40 joints working simultaneously and in unison.
"We spend a few years of our lives learning how to control our [joints] and our sense of balance and pushing that task down to a reflex," said Neuhaus. "When a one-year-old is learning to walk, it's at the forefront of their cognition. They're really thinking hard about how to do it. When you're older, you can walk and think about other things at the same time."
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