The robotics pioneer Rodney Brooks often begins speeches by reaching into his pocket, fiddling with some loose change, finding a quarter, pulling it out and twirling it in his fingers. The task requires hardly any thought. But as Dr. Brooks points out, training a robot to do it is a vastly harder problem for artificial intelligence researchers than IBM’s celebrated victory on “Jeopardy!” this year with a robot named Watson. Although robots have made great strides in manufacturing, where tasks are repetitive, they are still no match for humans, who can grasp things and move about effortlessly in the physical world. Designing a robot to mimic the basic capabilities of motion and perception would be revolutionary, researchers say, with applications stretching from care for the elderly to returning overseas manufacturing operations to the United States (albeit with fewer workers). Yet the challenges remain immense, far higher than artificial intelligence hurdles like speaking and hearing. “All these problems where you want to duplicate something biology does, such as perception, touch, planning or grasping, turn out to be hard in fundamental ways,” said Gary Bradski, a vision specialist at Willow Garage, a robot development company based here in Silicon Valley. “It’s always surprising, because humans can do so much effortlessly.” Recently at an SRI laboratory here, two Stanford University graduate students, John Ulmen and Dan Aukes, put the finishing touches on a significant step toward human capabilities: a four-finger hand that will grasp with a human’s precise sense of touch. Each three-jointed finger is made in a single manufacturing step by a three-dimensional printer and is then covered with “skin” derived from the same material used to make the touch-sensitive displays on smartphones. “Part of what we’re riding on is there has been a very strong push for tactile displays because of smartphones,” said Pablo Garcia, an SRI robot designer who is leading the design of the project, along with Robert Bolles, an artificial intelligence researcher. “We’ve taken advantage of these technologies,” Mr. Garcia went on, “and we’re banking on the fact they will continue to evolve and be made even cheaper.” Still lacking is a generation of software Still lacking is a generation of software that is powerful and flexible enough to do tasks that humans do effortlessly. That will require a breakthrough in machines’ perception. “I would say this is more difficult than what the Watson machine had to do,” said Gill Pratt, the computer scientist who is the program manager in charge of Darpa’s Autonomous Robot Manipulation project, called ARM. The “world is composed of continuous objects that have various shapes” that can obscure one another, he said. “A perception system needs to figure this out, and it needs the common sense of a child to do that.” At Willow Garage, Dr. Bradski and a group of artificial intelligence researchers and roboticists have focused on “hackathons,” in which the company’s PR2 robot has been programmed to do tasks like fetching beer from a refrigerator, playing pool and packing groceries. In May, with support from the White House Office of Science and Technology Policy, Dr. Bradski helped organize the first Solutions in Perception Challenge. A prize of $10,000 is offered for the first team to design a robot that is able to recognize 100 items commonly found on the shelves of supermarkets and drugstores. Part of the prize will be given to the first team whose robot can recognize 80 percent of the items. At the contest, held during a robotics conference in Shanghai, none of the contestants reached the 80 percent goal. The team that did best was the laundry-folding team from Berkeley, which has named its robot Brett, for Berkeley Robot for the Elimination of Tedious Tasks. Brett was able to recognize 68 percent of a smaller group of 50 objects. And the team has made progress in its quest to build a machine to do the laundry; it recently posted a new video showing how much it has sped up the robot. “Our end goal right now is to do an entire laundry cycle,” said Pieter Abbeel, a Berkeley computer scientist who leads the group, “from dirty laundry in a basket to everything stacked away after it’s been washed and dried.” Now the Defense Advanced Research Projects Agency, or DARPA, the Pentagon office that helped jump-start the first generation of artificial intelligence research in the 1960s, is underwriting three competing efforts to develop robotic arms and hands one-tenth as expensive as today’s systems, which often cost $100,000 or more. Last month President Obama traveled to Carnegie Mellon University in Pittsburgh to unveil a $500 million effort to create advanced robotic technologies needed to help bring manufacturing back to the United States. But lower-cost computer-controlled mechanical arms and hands are only the first step. There is still significant debate about how even to begin to design a machine that might be flexible enough to do many of the things humans do: fold laundry, cook or wash dishes. That will require a breakthrough in software that mimics perception. Today’s robots can often do one such task in limited circumstances, but researchers describe their skills as “brittle.” They fail if the tiniest change is introduced. Moreover, they must be reprogrammed in a cumbersome fashion to do something else. Many robotics researchers are pursuing a bottom-up approach, hoping that by training robots on one task at a time, they can build a library of tasks that will ultimately make it possible for robots to begin to mimic humans. Others are skeptical, saying that truly useful machines await an artificial intelligence breakthrough that yields vastly more flexible perception.