“The processing of images is typically very slow [for a robot], so a robot has difficulty reacting in time,” Ramos said in a statement. “Instead, we’d like to use the human’s natural reflexes and coordination. An example is walking, which is just a process of falling and catching yourself. That’s something that feels effortless to us, but it’s challenging to program into a robot to do it both dynamically and efficiently."
The tipping point
Walking, punching, kicking, swinging things through the air: These are all good examples of tasks that require both forward momentum and balance.
To help the robot master these kinds of movements, the researchers first had to figure out the 100-pound (45 kilograms) bot's tipping point, so to speak. To do this, they put load sensors on both of the robot's feet. These sensors measured the force exerted by each foot on the ground and were used to calculate the bot's center of pressure, or how it shifted its weight, as it performed different tasks.
Then, the researchers built the "human" portion of the human-machine interface. The researchers constructed a motorized platform on which the person controlling the bot stands. The human in control also wears the futuristic-looking exoskeleton, which fits around the waist. The exoskeleton is connected to the motorized platform, which in turn is connected to a computer.
The computer receives information about the robot's changing center of pressure and sends this information to the platform's motor. Finally, the motor applies force to the exoskeleton based on the bot's movements. In other words, whoever is wearing the exoskeleton gets knocked around as the bot moves its body.
“If the robot is leaning too far forward, the interface will push the operator in the opposite direction, to convey that the robot is in danger of falling," Albert Wang, a doctoral student working on the new interface, said in a statement.
So far, the interface has kept the bot from tumbling over as it punches through drywall and received repeated hits on its torso from a hammer. Next, the researchers would like to move on to more challenging tasks, such as having the bot swing an ax and open a spring-loaded door. These are the sorts of tasks that are particularly tough for bots to complete without falling over, according to Wang. But it might be easier for bots to do these jobs now that they have help from reflex-ready humans.