The researches enabled the robot to do the laundry without knowing how many and what type of clothes needed to be washed."The widely imagined helper robots of the future are expected to 'clear the table,' 'do laundry' or perform day-to-day tasks with ease," said Siddharth Srivastava, a scientist at the United Technologies Research Center, Berkeley.

The researchers' key insight was to use human behaviour - the almost unconscious action of pulling, stuffing, folding and piling as a template, adapting both the repetitive and thoughtful aspects of human problem-solving to handle uncertainty in their computed solutions.

Out of the 13 or so tasks involved in the laundry problem, the team's system was able to complete more than half of them autonomously and nearly completed the rest -- by far the most effective demonstration of laundering  for artificial intelligence (AI) to date, the researches noted.

The framework that Srivastava and his team developed combines several popular planning paradigms that have been developed in the past using complex control structures such as loops and branches and optimises them to run efficiently on modern hardware.

It also incorporates an effective approach for computing plans by learning from examples, rather than through rigid instructions or programmes.

Srivastava presented the robot at the recently concluded Association for Advancement of Artificial Intelligence conference in Austin, Texas.

 

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