Household robot can do your laundry

Researchers, including those of Indian-origin, have developed new algorithms that allow a robot to do laundry without any specific knowledge of what it has to wash.
University of California, Berkeley researchers Siddharth Srivastava, Abhishek Gupta and their colleagues from the University of Massachusetts in Amherst developed a new approach that allows a robot to plan its activity to accomplish an assigned task.
To Artificial Intelligence (AI) experts, programming a robot to do the laundry represents a challenging planning problem because current sensing and manipulation technology is not good enough to identify precisely the number of clothing pieces that are in a pile and the number that are picked up with each grasp.

People can easily cope with this type of uncertainty and come up with a simple plan. But roboticists for decades have struggled to design an autonomous system able to do what we do so casually - clean our clothes.
"The widely imagined helper robots of the future are expected to 'clear the table,' 'do laundry' or perform day-to-day tasks with ease," Srivastava said.
"Currently however, computing the required behaviour for such tasks is a challenging problem - particularly when there's uncertainty in resource or object quantities," he said.

The team has designed new algorithms that allow autonomous systems to deal with uncertainty.

The researchers used 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.
By doing so, they enabled a robot to do the laundry without knowing how many and what type of clothes needed to be washed.
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 AI to date.

Though laundry robots are an impressive, and potentially time-saving, application of AI, the framework that Srivastava and his team developed can be applied to a range of problems.
From manufacturing to space exploration to search-and-rescue operations, any situation where artificially intelligent systems must act, despite some degree of uncertainty, can be addressed with the method, researchers said.