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Showing posts with label robot. Show all posts
Showing posts with label robot. Show all posts

Friday, January 10, 2020

Two-legged robot mimics human balance while running and jumping

Two-legged robot mimics human balance while running and jumping


Rescuing victims from a burning building, a chemical spill, or any disaster that is inaccessible to human responders could one day be a mission for resilient, adaptable robots. Imagine, for instance, rescue-bots that can bound through rubble on all fours, then rise up on two legs to push aside a heavy obstacle or break through a locked door.
Engineers are making strides on the design of four-legged robots and their ability to run, jump and even do backflips. But getting two-legged, humanoid robots to exert force or push against something without falling has been a significant stumbling block.
Now engineers at MIT and the University of Illinois at Urbana-Champaign have developed a method to control balance in a two-legged, teleoperated robot -- an essential step toward enabling a humanoid to carry out high-impact tasks in challenging environments.
The team's robot, physically resembling a machined torso and two legs, is controlled remotely by a human operator wearing a vest that transmits information about the human's motion and ground reaction forces to the robot.
Through the vest, the human operator can both direct the robot's locomotion and feel the robot's motions. If the robot is starting to tip over, the human feels a corresponding pull on the vest and can adjust in a way to rebalance both herself and, synchronously, the robot.
In experiments with the robot to test this new "balance feedback" approach, the researchers were able to remotely maintain the robot's balance as it jumped and walked in place in sync with its human operator.
"It's like running with a heavy backpack -- you can feel how the dynamics of the backpack move around you, and you can compensate properly," says Joao Ramos, who developed the approach as an MIT postdoc. "Now if you want to open a heavy door, the human can command the robot to throw its body at the door and push it open, without losing balance."
Ramos, who is now an assistant professor at the University of Illinois at Urbana-Champaign, has detailed the approach in a study appearing in Science Robotics. His co-author on the study is Sangbae Kim, associate professor of mechanical engineering at MIT.
More than motion
Previously, Kim and Ramos built the two-legged robot HERMES (for Highly Efficient Robotic Mechanisms and Electromechanical System) and developed methods for it to mimic the motions of an operator via teleoperation, an approach that the researchers say comes with certain humanistic advantages.
"Because you have a person who can learn and adapt on the fly, a robot can perform motions that it's never practiced before [via teleoperation]," Ramos says.
In demonstrations, HERMES has poured coffee into a cup, wielded an ax to chop wood, and handled an extinguisher to put out a fire.
All these tasks have involved the robot's upper body and algorithms to match the robot's limb positioning with that of its operator's. HERMES was able to carry out high-impact motions because the robot was rooted in place. Balance, in these cases, was much simpler to maintain. If the robot were required to take any steps, however, it would have likely tipped over in attempting to mimic the operator's motions.
"We realized in order to generate high forces or move heavy objects, just copying motions wouldn't be enough, because the robot would fall easily," Kim says. "We needed to copy the operator's dynamic balance."
Enter Little HERMES, a miniature version of HERMES that is about a third the size of an average human adult. The team engineered the robot as simply a torso and two legs, and designed the system specifically to test lower-body tasks, such as locomotion and balance. As with its full-body counterpart, Little HERMES is designed for teleoperation, with an operator suited up in a vest to control the robot's actions.
For the robot to copy the operator's balance rather than just their motions, the team had to first find a simple way to represent balance. Ramos eventually realized that balance could be stripped down to two main ingredients: a person's center of mass and their center of pressure -- basically, a point on the ground where a force equivalent to all supporting forces is exerted.
The location of the center of mass in relation to the center of pressure, Ramos found, relates directly to how balanced a person is at any given time. He also found that the position of these two ingredients could be physically represented as an inverted pendulum. Imagine swaying from side to side while staying rooted to the same spot. The effect is similar to the swaying of an upside-down pendulum, the top end representing a human's center of mass (usually in the torso) and the bottom representing their center of pressure on the ground.
Heavy lifting
To define how center of mass relates to center of pressure, Ramos gathered human motion data, including measurements in the lab, where he swayed back and forth, walked in place, and jumped on a force plate that measured the forces he exerted on the ground, as the position of his feet and torso were recorded. He then condensed this data into measurements of the center of mass and the center of pressure, and developed a model to represent each in relation to the other, as an inverted pendulum.
He then developed a second model, similar to the model for human balance but scaled to the dimensions of the smaller, lighter robot, and he developed a control algorithm to link and enable feedback between the two models.
The researchers tested this balance feedback model, first on a simple inverted pendulum that they built in the lab, in the form of a beam about the same height as Little HERMES. They connected the beam to their teleoperation system, and it swayed back and forth along a track in response to an operator's movements. As the operator swayed to one side, the beam did likewise -- a movement that the operator could also feel through the vest. If the beam swayed too far, the operator, feeling the pull, could lean the other way to compensate, and keep the beam balanced.
The experiments showed that the new feedback model could work to maintain balance on the beam, so the researchers then tried the model on Little HERMES. They also developed an algorithm for the robot to automatically translate the simple model of balance to the forces that each of its feet would have to generate, to copy the operator's feet.
In the lab, Ramos found that as he wore the vest, he could not only control the robot's motions and balance, but he also could feel the robot's movements. When the robot was struck with a hammer from various directions, Ramos felt the vest jerk in the direction the robot moved. Ramos instinctively resisted the tug, which the robot registered as a subtle shift in the center of mass in relation to center of pressure, which it in turn mimicked. The result was that the robot was able to keep from tipping over, even amidst repeated blows to its body.
Little HERMES also mimicked Ramos in other exercises, including running and jumping in place, and walking on uneven ground, all while maintaining its balance without the aid of tethers or supports.
"Balance feedback is a difficult thing to define because it's something we do without thinking," Kim says. "This is the first time balance feedback is properly defined for the dynamic actions. This will change how we control a teleoperated humanoid."
Kim and Ramos will continue to work on developing a full-body humanoid with similar balance control, to one day be able to gallop through a disaster zone and rise up to push away barriers as part of rescue or salvage missions.
"Now we can do heavy door opening or lifting or throwing heavy objects, with proper balance communication," Kim says.
This research was supported, in part, by Hon Hai Precision Industry Co. Ltd. and Naver Labs Corporation.

Story Source:
Materials provided by Massachusetts Institute of Technology. Original written by Jennifer Chu. Note: Content may be edited for style and length.

Tuesday, November 26, 2019

Trash talk hurts, even when it comes from a robot

Trash talk hurts

Trash talking has a long and colorful history of flustering game opponents, and now researchers at Carnegie Mellon University have demonstrated that discouraging words can be perturbing even when uttered by a robot.
The trash talk in the study was decidedly mild, with utterances such as "I have to say you are a terrible player," and "Over the course of the game your playing has become confused." Even so, people who played a game with the robot -- a commercially available humanoid robot known as Pepper -- performed worse when the robot discouraged them and better when the robot encouraged them.
Lead author Aaron M. Roth said some of the 40 study participants were technically sophisticated and fully understood that a machine was the source of their discomfort.
"One participant said, 'I don't like what the robot is saying, but that's the way it was programmed so I can't blame it,'" said Roth, who conducted the study while he was a master's student in the CMU Robotics Institute.
But the researchers found that, overall, human performance ebbed regardless of technical sophistication.
The study, presented last month at the IEEE International Conference on Robot & Human Interactive Communication (RO-MAN) in New Delhi, India, is a departure from typical human-robot interaction studies, which tend to focus on how humans and robots can best work together.
"This is one of the first studies of human-robot interaction in an environment where they are not cooperating," said co-author Fei Fang, an assistant professor in the Institute for Software Research. It has enormous implications for a world where the number of robots and internet of things (IoT) devices with artificial intelligence capabilities is expected to grow exponentially. "We can expect home assistants to be cooperative," she said, "but in situations such as online shopping, they may not have the same goals as we do."
The study was an outgrowth of a student project in AI Methods for Social Good, a course that Fang teaches. The students wanted to explore the uses of game theory and bounded rationality in the context of robots, so they designed a study in which humans would compete against a robot in a game called "Guards and Treasures." A so-called Stackelberg game, researchers use it to study rationality. This is a typical game used to study defender-attacker interaction in research on security games, an area in which Fang has done extensive work.
Each participant played the game 35 times with the robot, while either soaking in encouraging words from the robot or getting their ears singed with dismissive remarks. Although the human players' rationality improved as the number of games played increased, those who were criticized by the robot didn't score as well as those who were praised.
It's well established that an individual's performance is affected by what other people say, but the study shows that humans also respond to what machines say, said Afsaneh Doryab, a systems scientist at CMU's Human-Computer Interaction Institute (HCII) during the study and now an assistant professor in Engineering Systems and Environment at the University of Virginia. This machine's ability to prompt responses could have implications for automated learning, mental health treatment and even the use of robots as companions, she said.
Future work might focus on nonverbal expression between robot and humans, said Roth, now a Ph.D. student at the University of Maryland. Fang suggests that more needs to be learned about how different types of machines -- say, a humanoid robot as compared to a computer box -- might invoke different responses in humans.
In addition to Roth, Fang and Doryab, the research team included Manuela Veloso, professor of computer science; Samantha Reig, a Ph.D. student in the HCII; Umang Bhatt, who recently completed a joint bachelor's-master's degree program in electrical and computer engineering; Jonathan Shulgach, a master's student in biomedical engineering; and Tamara Amin, who recently finished her master's degree in civil and environmental engineering.
The National Science Foundation provided some support for this work.

Story Source:
Materials provided by Carnegie Mellon University. Original written by Byron Spice. Note: Content may be edited for style and length.