Today’s robots may be astonishing, scary, or militarily useful, but they rarely move with all the occasional grace, jitters, and other subtle quirks that humans have. That may change with some new research from Georgia Tech.
Though robots are increasingly hitting the headlines, and some of them are getting clever at replicating animal locomotion (visions of Boston Dynamics’ Big Dog will skitter across your memory at this point) the devices are still driven by motors, gears, and actuators commanded by cold, hard silicon so they tend to operate with obviously artificial movements. This means they miss out on some of the non-verbal modes of communication that humans use all the time–often without thinking about them–which also impacts on how humans perceive the bots.
Which is where research from Georgia Tech comes in. Based on their research droid Simon who looks distinctly robotic with a comedic head and glowing “ears,” a team working in the Socially Intelligent Machines Lab has been trying to teach Simon to move like humans do–forcing less machine-like gestures from his solid limbs. The trick was to record real human subjects performing a series of moves in a motion-capture studio, then taking the data and using it to program Simon, being careful (via a clever algorithm) to replicate the fluid multiple-joint rotations a human body does when swinging a limb between one position and the next, and which robot movements tend to avoid.
Then the team got volunteers to observe Simon in action, and asked them to identify the kinds of movements he was making. When a more smooth, fluid robot movement was made, the volunteers were better at identifying the gesture compared to a more “robotic” movement. To double-check the algorithm’s effectiveness the researchers then asked the human volunteers to mimic the gestures they thought the robot was making, tapping into the unconscious part of their minds that recognize human tics: And again, the volunteers were better at correctly mimicking the gesture when the human-like algorithm was applied to Simon’s moves.
In the future, Simon’s algorithm will be tweaked to include deliberate imprecisions to more closely copy how human movements work, because if you think about it though you may repeat a gesture over and over again with your body (something like typing on a keyboard or nodding your head in affirmation) each time you do your brain commands your muscles differently, and your muscles and skeleton aren’t built for precision replication.
Why’s this research important? Because as robots become increasingly a part of every day human life, we need to trust them and interact with them normally. Just as other research tries to teach robots to move in ways that can’t hurt us, this work will create robots that move in subtle ways to communicate physically with nearby people, aiding their incorporation into society. In medical professional roles, which are some of the first places humanoid robots may find work, this sort of acceptance could be absolutely crucial.
To read more news like this, follow Fast Company on Twitter: Click here.