Engineers decoded a vital human physical dynamic skill of maintaining whole-body balance into a mathematical equation. This numerical formula was used to program a robot, Mercury. With a margin of error within 2 centimeters, this has implications in emergency response, to defense, to entertainment
Researchers in the Cockrell School of Engineering at the University of Texas at Austin have successfully demonstrated a novel approach to human-like balance in a biped robot. Dynamic human-body-like movement is far harder to achieve for a robot without ankle control than for one equipped with actuated, or jointed, feet.
So, the team used an efficient whole-body controller to effectively send and receive data, so as to inform the robot about the best possible move to make next in response to a collision. They also applied a mathematical technique known as inverse kinematics, along with low-level motor position controllers.
The robot, Mercury, was developed specifically for this purpose, over a period of six years. However, the fundamental equations supporting this technique in understanding of human locomotion are universally applicable to any similar, personified artificial intelligence (AI) and robotics research.