Your household robot won’t just clean and make repairs, it will come up with clever, novel solutions to problems by improvising. This hallmark of artificial intelligence is a little closer to reality thanks to a robot named Kurt3D. In a recent test, Kurt3D figured out how to activate a switch and open a door by improvising, using a limited set of instructions. The key to this A.I. breakthrough is a new way of teaching computers about objects by teaching them what something is for rather than simply what it is.
A great deal of A.I. research has focused on teaching computers to identify lists of objects and people. The Multi-sensory Autonomous Cognitive Systems (MACS) project uses a different paradigm – affordance learning. Instead of identifying a specific object as a hammer, an affordance-based system learns the parameters of what makes a hammer useful for hammering. It needs a shaft for leverage, a weight at the end and a flat surface for hammering. Then, if the robot needs to find something with which to hammer, it wouldn’t be limited by a narrow visual recognition algorithm for a hammer. It could search for any object suitable for the purpose.
The only given parameters in the Kurt3D test stated that a door switch could be activated by placing a certain weight on a pressure sensitive plate. Kurt3D was able to examine the room, identify an appropriate object, pick it up, place it on the plate, and move through the open door. Photo by: Fraunhofer AIS.
What Can I, Robot, Do With That? [Science Daily]
