MIT‘s two-legged robot named HERMES is wreaking controlled havoc: punching through drywall, smashing soda cans, kicking over trash buckets, and karate-chopping boards in half.
The robots actions, however, are not its own. Just a few feet away, PhD student Joao Ramos stands on a platform, wearing an exoskeleton of wires and motors.
Ramos’ every move is translated instantly to HERMES, much like a puppeteer controlling his marionette. As Ramos mimes punching through a wall, the robot does the same. When the robot’s fist hits the wall, Ramos feels a jolt at his waist. By reflex, he leans back against the jolt, causing the robot to rock back, effectively balancing the robot against the force of its punch.
The exercises are meant to demonstrate the robot’s unique balance-feedback interface. Without this interface, while the robot may successfully punch through a wall, it would also fall headlong into that wall. The interface allows a human to remotely feel the robot’s shifting weight, and quickly adjust the robot’s balance by shifting his own weight. As a result, the robot can carry out momentum-driven tasks — like punching through walls, or swinging a bat — while maintaining its balance.
The interface takes advantage of a human’s split-second reflexes, which give the robot much faster reaction times than robots that adjust their balance based on visual feedback from onboard cameras.
Ultimately, Ramos and his colleagues envision deploying HERMES to a disaster site, where the robot would explore the area, guided by a human operator from a remote location.
The researchers will present a paper on the interface at the IEEE/RSJ International Conference on Intelligent Robots and Systems in September.
To give the human operator a sense of the robot’s balance, the team first looked for a way to measure the robot’s center of pressure, or weight distribution, which indicates its balance and stability.
The researchers worked with HERMES, a 100-pound biped robot designed by the team, along with the interface, for disaster response. They outfitted the robot’s feet with load sensors that measure the force exerted by each foot on the ground.
Depending on the forces measured, the researchers calculated the robot’s center of pressure, or where it was shifting its weight. They then mapped out a polygonal area, the edges of which represent each of the robot’s feet. They determined that if the robot’s center of pressure strayed toward the edges of this support polygon, the robot was in danger of falling.
They then built the balance-feedback interface: a large polygonal platform equipped with motors, and an exoskeleton of metal bars and wires that attaches to a person’s waist — essentially, the human body’s center of mass. With computer software, the researchers translated the robot’s center of pressure to the platform’s motors, which apply comparable force to the exoskeleton, pushing a person back and forth as the robot shifts its weight.
In experiments to test the interface, the researcher repeatedly struck the robot’s torso with a hammer. Ramos, standing on the platform, was unaware of when the hammer would strike. As they struck the robot, the platform exerted a similar jolt on Ramos, who reflexively shifted his weight to regain his balance, causing the robot to also catch itself.
The team also tested whether the robot kept its balance while punching through drywall. The platform pushed forward on Ramos as the robot made contact with the wall. In response, Ramos rocked back on his heels, causing the robot to do the same.
