New York, Jan 20 (IANS): In a novel bid to make future robots understand human movement better and act more efficiently, researchers have created human arm sensors - a first.

These unique arm sensors can 'read' a person's muscle movements - thus creating a movement that is more friendly to robots - and simultaneously making robots more intelligent, said a press release issued by Georgia Institute of Technology in the US.

How does it work?

The sensors, attached to a human's forearm, send information to the robot - allowing it to anticipate the muscle movements and correct its own.

The system is intended to improve time, safety and efficiency in manufacturing plants, said the release.

"We tried to solve the problem where a person's muscle stiffness is never constant and a robot nearby does not always know how to correctly react to the movement,” said Billy Gallagher, a recent Georgia Tech PhD graduate in robotics who led the project.

For example, as human operators shift the lever forward or backward, the robot recognises the command and moves appropriately.

But when they want to stop the movement and hold the lever in place, people tend to stiffen and contract muscles on both sides of their arms.

Here, the robot gets confused.

“It doesn't know whether the force is purely another command that should be amplified or 'bounced' force due to muscle co-contraction,” said Jun Ueda, professor in the Woodruff School of Mechanical Engineering.

The robot responds to that bounced force, creating vibration. The human operators also react, creating more force by stiffening their arms. The situation and vibrations become worse.

The Georgia Tech system eliminates the vibrations by using sensors worn on a controller's forearm.

The devices send muscle movements to a computer, which provides the robot with the operator's level of muscle contraction.

“Instead of having the robot react to a human, we give it more information,” said Gallagher.

Modelling the operator in this way allows the robot to actively adjust to changes in the way the operator moves, said the study.