Robotic Arm Can Catch Things Better Than You Can

This Robotic Arm Is Better At Catching Stuff Than You Are

This rather funky looking mechanical arm is leading the way in the field of robotic catch.

Developed by EPFL researchers, it is capable of tracking and catching an object in less than five-hundredths of a second.

Even more impressively, it can handle irregular shaped items such as a tennis racket.

It consists of three joints and a hand with four fingers and was developed by EPFL's Learning Algorithms and Systems Laboratory.

Head of the lab, Aude Billard, said: "Increasingly present in our daily lives and used to perform various tasks, robots will be able to either catch or dodge complex objects in full-motion,

"Not only do we need machines able to react on the spot, but also to predict the moving object's dynamics and generate a movement in the opposite direction.

It is hoped such a system could be used in space to protect satellites from debris hurtling towards it.

The arm's programmers used a process of trial and error to make it 'learn', manually guiding it towards objects until it can work out trajectories itself.

The research was conducted with a ball, an empty bottle, a half full bottle, a hammer and a tennis racket. These five common objects were selected because they offer a varied range of situations in which the part of the object that the robot has to catch (the handle of the racket, for example) does not correspond to its centre of gravity.

The case of the bottle even offers an additional challenge since its centre of gravity moves several times during its trajectory. When projected into the air, all these items will make even more complex movements, often involving several axes. As a result, when the moving objects are submitted to the robot’s abilities, the outcomes turn out quite interesting.

In the first learning phase, objects are thrown several times in the robot’s direction. Through a series of cameras located all around it, the robot creates a model for the objects’ kinetics based on their trajectories, speeds and rotational movement.

Scientists translate it into an equation which then allows the robot to position itself very quickly in the right direction whenever an object is thrown. During the few milliseconds of the approach, the machine refines and corrects the trajectory for a real-time and high precision capture. This efficiency is further enhanced by the development of controllers that couple and synchronize the movements of the hand and fingers.

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