They appear in everything from amusement park rides to motion pictures - animatronic characters that substitute electromechanical systems for muscle and sinew. Whether a 26-ft-high version of a football player, a talking lion, or a long-dead president like Abraham Lincoln, animatronic characters take us beyond the bounds of reality. With the aid of motion control elements, they make the impossible possible.

Like machine vision, animatronics provides a vivid example of how biological systems make incredibly complex problems appear simple. Let’s forget about the challenge of standing or walking. Just creating natural-looking expressions using electromechanical systems is extremely challenging. The average human face features 40 to 50 separate muscles. We can smile with barely a thought, in an instant. Now consider trying to duplicate that electromechanically, performing path planning, coordinating axes, and handing down commutation commands to 40 separate motors in milliseconds.

The developers of the Albert Einstein humanoid robot (Albert-Hubo - pictured) have done nearly that. A collaboration between Hanson Robotics and the Korea Advanced Institute of Science and Technology (KAIST), with support from the University of Texas, the Albert-Hubo can not only walk un-tethered and unsupported (see video here), it features a range of natural expressions and the ability to recognize people in its field of view and turn to address them.

Emulating muscle movement in the face alone requires 32 DC gearmotors, says David Hanson founder and CEO of Hanson Robotics, which built the head portion of the robot. Because the motors are reversible, each simulates the movement of two muscle groups, for a total of 64 muscles. Given the space constraints, the motors needed to be small diameter, high-torque-density devices. The Hansen Robotics team chose three different motors the smallest of which is less than a centimeter in diameter. This model generates 2.8 kg/cm of torque; and with an additional gearbox provides a whopping 6000:1 reduction ratio. The motors either pull on drive linkages attached to the skin or press against it with steel pins and levers. Integrated drive electronics simplify assembly and operation, and encoders provide condition and position feedback.

For years, the default material to simulate human flesh was rubber. Hanson Robotics has developed a more compliant, porous material dubbed Frubber that more effectively simulates the response of human tissue. The result is the eerily realistic. Better yet, the force required to deform the material is 23 times less than that of rubber, cutting demands on motor torque and power, which increases battery life.

Taking Control

However appealing smart components might be, this type of tightly-coupled problem requires centralized control. Albert-Hubo incorporates two controllers: one for the facial expressions and the other to run the motors in the body that allow the robot to walk. The act of walking is essentially a controlled fall past a zero momentum point, involving tightly coupled weight shifts. The Einstein robot accomplishes this with a combination of inertial sensors, gyro accelerometer, and very fast feedback PID loops. The result is natural looking gestures that escaped the artificial-looking constant-velocity movements so often seen in animatronic devices.

In addition to facial expressions, the robot can move its eyes and adjust the tilt and rotational angle of its head. Instead of a motion controller, the group uses a PC, which can handle higher-level calculations. Image sensors in the eyes allow the robot to recognize people in its field of view and turn toward them using simple visual servoing techniques, for example. The sensors send the information and we run our perceptual algorithms on it to correlate it with a [3D space] model we call the egosphere,” says Hanson. “The robot will remember that people have been seen in that space and make some probability predictions of the likelihood of them to be in a particular position. Then it does a correlation of its head and eye kinematics relative to that three space so that it can calculate how to servo over to look at a particular location while maintaining expressive use of the head.”