
A collaboration between UW developmental psychologists and computer scientists aims to enable robots to learn in the same way that children naturally do. The team used research on how babies follow an adult’s gaze to “teach” a robot to perform the same task.University of Washington
Babies learn about the world by exploring how their bodies move in space, grabbing toys, pushing things off tables and by watching and imitating what adults are doing.
But when roboticists want to teach a robot how to do a task, they typically either write code or physically move a robot’s arm or body to show it how to perform an action.
Now a collaboration between University of Washington developmental psychologists and computer scientists has demonstrated that robots can “learn” much like kids — by amassing data through exploration, watching a human do something and determining how to perform that task on its own.
“You can look at this as a first step in building robots that can learn from humans in the same way that infants learn from humans,” said senior author Rajesh Rao, a UW professor of computer science and engineering.
“If you want people who don’t know anything about computer programming to be able to teach a robot, the way to do it is through demonstration — showing the robot how to clean your dishes, fold your clothes, or do household chores. But to achieve that goal, you need the robot to be able to understand those actions and perform them on their own.”
The research, which combines child development research from the UW’s Institute for Learning & Brain Sciences Lab (I-LABS) with machine learning approaches, was published in a paper in November in the journal PLOS ONE.
In the paper, the UW team developed a new probabilistic model aimed at solving a fundamental challenge in robotics: building robots that can learn new skills by watching people and imitating them.
The roboticists collaborated with UW psychology professor and I-LABS co-director Andrew Meltzoff, whose seminal research has shown that children as young as 18 months can infer the goal of an adult’s actions and develop alternate ways of reaching that goal themselves.
In one example, infants saw an adult try to pull apart a barbell-shaped toy, but the adult failed to achieve that goal because the toy was stuck together and his hands slipped off the ends. The infants watched carefully and then decided to use alternate methods — they wrapped their tiny fingers all the way around the ends and yanked especially hard — duplicating what the adult intended to do.
Children acquire intention-reading skills, in part, through self-exploration that helps them learn the laws of physics and how their own actions influence objects, eventually allowing them to amass enough knowledge to learn from others and to interpret their intentions. Meltzoff thinks that one of the reasons babies learn so quickly is that they are so playful.
“Babies engage in what looks like mindless play, but this enables future learning. It’s a baby’s secret sauce for innovation,” Meltzoff said. “If they’re trying to figure out how to work a new toy, they’re actually using knowledge they gained by playing with other toys. During play they’re learning a mental model of how their actions cause changes in the world. And once you have that model you can begin to solve novel problems and start to predict someone else’s intentions.”
Rao’s team used that infant research to develop machine learning algorithms that allow a robot to explore how its own actions result in different outcomes. Then the robot uses that learned probabilistic model to infer what a human wants it to do and complete the task, and even to “ask” for help if it’s not certain it can.
The team tested its robotic model in two different scenarios: a computer simulation experiment in which a robot learns to follow a human’s gaze, and another experiment in which an actual robot learns to imitate human actions involving moving toy food objects to different areas on a tabletop.
In the gaze experiment, the robot learns a model of its own head movements and assumes that the human’s head is governed by the same rules. The robot tracks the beginning and ending points of a human’s head movements as the human looks across the room and uses that information to figure out where the person is looking. The robot then uses its learned model of head movements to fixate on the same location as the human.
The team also recreated one of Meltzoff’s tests that showed infants who had experience with visual barriers and blindfolds weren’t interested in looking where a blindfolded adult was looking, because they understood the person couldn’t actually see. Once the team enabled the robot to “learn” what the consequences of being blindfolded were, it no longer followed the human’s head movement to look at the same spot.
Read more: UW roboticists learn to teach robots from babies
The Latest on: Robots that learn
[google_news title=”” keyword=”robots that learn” num_posts=”10″ blurb_length=”0″ show_thumb=”left”]
via Google News
The Latest on: Robots that learn
- Robots to start scrubbing public toilets in early 2024on December 3, 2023 at 8:46 pm
The robot's public testing phase will begin in the second quarter ... malls and hotels in stints between January and September 2023. "It was a very important learning process for us," Nguyen told The ...
- Robot chemist powered by artificial intelligence could create oxygen needed for humans colonising Mars: studyon December 3, 2023 at 4:52 pm
A robot chemist powered by artificial intelligence could solve the puzzle of providing oxygen to humans on Mars, according to the results of a new study.
- We don't know what we don't know, but robots couldon December 3, 2023 at 4:50 pm
Modern robots know how to sense their environment and respond to language, but what they don’t know is often more important than what they do know. Teaching robots to ask for help is key to making ...
- Scientists Build Biological Robots From Human Cellson December 2, 2023 at 2:30 am
Researchers have engineered tiny robots made from human cells that could potentially be used to help heal wounds, regenerate tissue, and even treat diseases. As detailed in their new study published ...
- Code Warriors: Meet the Top Coding Robots Revolutionizing Fun and Learningon December 1, 2023 at 2:16 pm
You can get coding robots for kids who are as young as 3, and cool coding robots for teens, and every age in-between. Coding is a real boon to kids learning according to the University of Texas, ...
- How Robots Are Learning to Ask for Helpon November 30, 2023 at 4:00 pm
Engineers from these prestigious institutions have developed an innovative method that teaches robots a crucial skill: recognizing when they need help and how to ask for it. This development marks a ...
- Humanoid Robots and the AI That Drives Themon November 30, 2023 at 6:24 am
As the humanoid robots move around their environment, the AI is what allows the robot to capture information through cameras and LiDAR sensors, analyze that data, make inferences, and then move or act ...
- Humanoid robots are here, but they’re a little awkward. Do we really need them?on November 28, 2023 at 8:24 pm
All the attention — and money — poured into making ungainly humanoid machines might make the whole enterprise seem like a futile hobby for wealthy technologists, but for some pioneers of legged robots ...
- An approach that allows robots to learn in changing environments from human feedback and explorationon November 28, 2023 at 4:50 am
To best assist humans in real-world settings, robots should be able to continuously acquire useful new skills in dynamic and rapidly changing environments. Currently, however, most robots can only ...
- A sensing paw that could improve the ability of legged robots to move on different terrainson November 27, 2023 at 9:41 am
Legged robots that artificially replicate the body structure and movements of animals could efficiently complete missions in a wide range of environments, including various outdoor natural settings.
via Bing News