The groom is a robotics researcher. The bride works at a robotics firm. Robots brought them together. So when it came time to plan their wedding, the choice only seemed natural: A robot would conduct the ceremony.
The wedding took place today in Tokyo, according to this AP report. The groom was Tomohiro Shibata, a professor of robotics at the Nara Institute of Science and Technology in central Japan; the bride was Satoko Inoue, who works at famed robotics firm Kokoro.
Leading the ceremony was a little humanoid robot called I-Fairy with a high-pitch voice and flashing eyes. Kokoro, which unveiled the robot early this year, designed the I-Fairy as a robot receptionist and entertainer. It sells for 6.3 million yen (US $68,000).
The robot has a humanoid body in a sitting posture and, as the company puts it, its appearance was "based on the image of a lovely fairy." It can talk, gesture with its arms, and detect the presence of a person, according to this story in the Japanese blog Node.
Kokoro says this was the first time a robot celebrated a wedding.
At one point the robot told the groom: "Please lift the bride's veil."
Is it a sculpture? Is it a robot? The Balancing Cube is both.
The Balancing Cube is a robotic sculpture that can stand on any of its corners. Pendulum-like modules, located on the inner faces of the cube, constantly adjust their positions to shift the structure's center of gravity and keep it balanced. The cube remains stable even if you poke it. But not too hard!
Created by Raffaello D'Andrea, Sebastian Trimpe, and Matt Donovan at ETH Zurich, the contraption is half art and half technology. They got their inspiration from a Cirque du Soleil performance in which acrobats use their bodies to support each other and balance together in seemingly impossible positions.
See the result in the video below. I love the part when Trimpe pushes the cube slightly and its balancing mechanisms respond, the motors screeching as if he were teasing a living creature.
So how does it work?
The Balancing Cube is an example of a distributed control platform. Each module [see illustration below] is a self-contained unit with a computer, battery, motor, and inertial sensors (a tri-axis accelerometer and tri-axis rate gyro). So instead of relying on a centralized controller, the modules share their inertial data through a bus network. Then each module combines its own data with the shared data to determine the orientation of the cube -- and command its motor accordingly.
In other words, each module makes its own computations and moves its own motor, but as a result the combined motion keeps the system stable -- just like the Cirque du Soleil acrobats.
D'Andrea and Trimpe discussed the cube's control scheme last week at the IEEE International Conference on Robotics and Automation, in Anchorage, Alaska.
Their control algorithm uses inertial data to estimate how the cube is oriented relative to gravity and how fast it is moving. But this estimate is independent of the rigid body dynamics of the cube; that is, the algorithm doesn't require a dynamic model of the cube, and the method works both in static conditions and for when the structure is in motion.
The cube, made of aluminum, is 1.2 meter on its sides and stands about 2 m tall. It may look like a star, but that's because its faces consist of X-shaped elements. It's cubic shape becomes apparent if you imagine lines connecting its corners [see image above]. (Think of Isamu Noguchi's Red Cube in New York.)
The goal of the project was more than just building a high-tech piece of art. The researchers wanted to investigate the advantages and limits of distributed control. In particular, they knew that the balancing mechanisms didn't need to share all their sensor data, but they wanted to find out which pieces they did need to share.
In terms of hardware, they focused on a modular design, trying to create a balancing system that would consist entirely of self-contained mechanisms. Indeed, you can use their mechanisms to balance not only a cube but also other shapes.
A final but critical design requirement: the hardware had to be robust enough to withstand repeated falls.
Images and video: Raffaello D'Andrea and Sebastian Trimpe/Institute for Dynamic Systems and Control - ETH Zurich
Technology taking jobs is a notion that probably dates back to the invention of the wheel. After all, it took four bearers to carry the emperor and only one to pull a chariot!
The problem is that most people stop thinking after the first domino falls instead of following the chain of events further on. Let's continue the chain: Once the wheel is invented, more people can travel comfortably, goods can be carried farther, better roads are built and commerce thrives. A few bearers of the ruling class have to find new work, the remainder of the world benefits and thousands of jobs are created.
Let's fast-forward through history and take a look at the tractor. Now it happens that my grandfather bred workhorses. The family oral history has it that, upon the introduction of Henry Ford's tractor in the 1920s, the price of workhorses dropped 10 percent per week. My grandfather lost his farm, moved his family to Florida where my father at age 14 had the only job in this family of six, delivering newspapers. However, the advent of the tractor and modern farming techniques transformed the United States from a country where 40 percent of the population needed to farm to one in which 2 percent of the population could feed the other 98 percent. This freed a larger proportion of young adults to attend college and start the computer revolution that has created millions of jobs in the U.S. and worldwide.
Did people lose jobs to computers? Yes, a number of secretaries had to upgrade their skills, and executives who refused to learn to type had a tough time of it, just to cite two examples. But these jobs were replaced by tens of thousands of high-paying software engineering positions, plus computer installers, computer operators, data storage firms and more.
Simplistic thinking visualizes a fixed pool of jobs, with new technology taking some away. In reality, new technologies create new opportunities for many more people, specially our children. In the case of robots, the direct new jobs involve designing, building, programming, integrating, installing, servicing, maintaining, managing and refining the machines. Robots will enable humans to work in hostile environments where they could never work before: for instance, farming the ocean floor, mining super subterranean excavations, manufacturing in space and in Antarctica all become realistic endeavors. Building on nano- and cosmic scales begin to become practicable. The limited imaginations that believe jobs will stay the same, except that robots will do them all, should take a look around them.
If it were true that technology makes people poorer, would we not find evidence of that all around us? Technology-poor countries would have full employment and technology-rich countries would have the lowest GDP per person. Instead, in technology-rich nations, so-called "poor" people often own cars and televisions, have a roof over their head and food for their tables.
Of course, anyone can argue that material wealth does not make for spiritual wealth; that's a matter for philosophers to wrestle with. And certainly there is room for improving systems for helping those in transition between jobs. But finding evidence that technological advance decreases material wealth for the general population is very difficult. Technology raises the floor for all; it is the great uplifter.
Jeanne Dietsch is co-founder and CEO of MobileRobots, based in Amherst, N.H.
They taught the car to accelerate in reverse up to 25 miles per hour, then suddenly hit the brakes, turn the wheel, and start a 180-degree skid--ending up right in a desired parking spot. It's not just a cool stunt--this research should give autonomous cars greater flexibility to deal with unexpected situations.
Reliably executing such a stunt isn't easy. "Junior" (as the car is known) usually operates under closed-loop control, where real-time sensor data is used to continually adjust the controls. This works well for driving the car in a straight line, where the physics of the car's motion are pretty straightforward to model. Unfortunately, the dynamics model tends to break down as the car enters the complex sliding turn. In the first clip of the video below, you can see Junior miss the mark under this type of control.
As an alternate approach, the team "taught" Junior the stunt through a basic demonstration. The researchers found that even though the sliding is complex to model, it's a highly deterministic motion--by just blindly repeating the control inputs from the demonstration, the car usually ended up in the same place. But as you can see in the second attempt in the video, this open-loop control method also has a weakness: errors in the straight approach go uncorrected and cause big differences in Junior's final position.
So to get the best result, the team combined approaches: keeping the car under closed-loop control during the well-modeled approach section, and then letting it transition to open-loop control for the final slide.
Most impressively, the Stanford team allowed the car to determine for itself which approach was better and when to smoothly switch between the two. The result (the third attempt in the video) lands the car right on target. For testing purposes the team decided to use cones rather than actual cars. Just in case.
I have to admit that I'm a sucker for simple solutions to difficult problems. At ICRA this week, one of the cleverest new designs (and winner of the award for best video) was for a small tube climbing robot. The Biorobotics lab and Manipulation lab at Carnegie Mellon University have been working for several years on dynamic climbing bots that can climb between walls without any special attachment mechanism. But they wanted to come up with a smaller design that could make it up three-dimensional tubes.
The result is this little device. It's simple motor turns an unbalanced mass at a uniform velocity. As the mass swings around, it causes the robot to bounce back and forth between the tube walls. Two rubber o-rings let the researches specify the exact contact points and increase friction with the walls.
This isn't the first tube-climbing, vibrating robot, but it has some distinct advantages. Earlier designs relied on fibers or bristles to create anisotropic friction with the walls and vibration caused motion in the direction of lowest friction. The problem with these designs comes when you need to remove the robot--now you're forced to work against the maximum friction.
What's most impressive about Carnegie Mellon's new bot is its speed, versatility, and payload capability. In the video, you can see that it travels up to 20 body-lengths per second and has a payload capacity of roughly 5x it's weight. The robot can even climb different sized tubes, although at different rates.
The researchers say they weren't application driven, but it's not hard to imagine such a simple device coming in handy for navigating tubing quickly.
(Video courtesy of Amir Degani, Siyuan Feng, Howie Choset, and Matthew T. Mason)
UPDATE:It turns out that the courageous individual in the video is Sami Haddadin, the study's lead author, who was clearly confident in the collision-detection system he devised. I incorporated additional details he gave me.
The idea of a robot in the kitchen cooking us meals sounds great. Just watch out when the automaton is handling the knives!
To find out what would happen if a robot holding a sharp tool accidentally struck a person, German researchers set out to perform a series of stabbing, puncturing, and cutting experiments.
They fitted an articulated robotic arm with various tools (scalpel, kitchen knife, scissors, steak knife, screwdriver) and programmed it to execute different striking maneuvers. They used a block of silicone, a pig's leg, and at one point a human volunteer's bare arm as the, uh, test surface.
The researchers -- Sami Haddadin, Alin Albu-Schaffer, and Gerd Hirzinger from the Institute of Robotics and Mechatronics, part of DLR, the German aerospace center, in Wessling, Germany -- presented their results today at the IEEE International Conference on Robotics and Automation, in Anchorage, Alaska.
The main goal of the study was to understand the biomechanics of soft-tissue injury caused by a knife-wielding robot. But the researchers also wanted to design and test a collision-detection system that could prevent or at least minimize injury. Apparently the system worked so well that in some cases the researchers were willing to try it on human subjects.
We applaud the guy [editor's note: see update above] at the end of the video who put his body on the line in the name of robotic science.
Warning: Some people may consider content graphic or upsetting.
The researchers acknowledge that there are huge reservations about equipping robots with sharp tools in human environments. It won't happen any time soon. (Sorry, you'll still have to chop that cucumber salad yourself). But they argue that only by getting more data can roboticists build safer robots.
The experiments involved the DLR Lightweight Robot III, or LWRIII, a 7 degrees-of-freedom robot manipulator with a 1.1 meter reach and moderately flexible joints. The robot, which weighs 14 kilograms, is designed for direct physical interaction and cooperation with humans.
The tools the researchers tested included [photo, right]: (1) scalpel; (2) kitchen knife; (3) scissors; (4) steak knife; (5) screwdriver.
The researchers performed two types of experiments: stabbing and cutting, testing the different tools striking at various speeds, with and without the collision-detection system active.
In most cases, the contact resulted in deep cuts and punctures, with potentially lethal consequences. But remarkably, the collision-detection system was able to reduce the depth of the cuts and in a few cases even prevent penetration altogether.
Although the robotic arm has a force-torque sensor on its wrist, this sensor is not used in the collision-detection system; it only serves as a measurement reference in the experiment. "The collision detection and reaction," Haddadin told me, "is based on a very good dynamics model of the robot and the fact that, unlike other robots, we have torque sensors and position sensors in every joint."
With the dynamics model (which includes rigid body dynamics, joint elasticity, and motor model) and the sensor measurements, the robot can detect a collision nearly instantaneously. (The control system relies on a "nonlinear disturbance observer.")
"This method does not require any additional external sensors and only relies on the internal capabilities of the robot," says Haddadin.
This is the first study to investigate soft-tissue injuries caused by robots and sharp instruments. Previous studies by the same researchers, as well as other groups, have focused on blunt collisions involving non-sharp surfaces.
The video below shows impact experiments using crash-test dummies and large industrial robots. Ouch.
To be useful in human environments, robots must be able to do things that people do on a daily basis -- things like opening doors, drawers, and cabinets. We perform those actions effortlessly, but getting a robot to do the same is another story. Now Georgia Tech researchers have come up with a promising approach.
Professor Charlie Kemp and Advait Jain at Georgia Tech's Healthcare Robotics Laboratory have programmed a robot to autonomously approach and open doors and drawers. It does that using omni-directional wheels and compliant arms, and the only information it needs is the location and orientation of the handles.
The researchers discussed their results yesterday at the IEEE International Conference on Robotics and Automation, in Anchorage, Alaska, where they presented a paper, "Pulling Open Doors and Drawers: Coordinating an Omni-Directional Base and a Compliant Arm with Equilibrium Point Control."
One of the neat things about their method is that the robot is not stationary while opening the door or drawer. "While pulling on the handle," they write in their paper, "the robot haptically infers the mechanism's kinematics in order to adapt the motion of its base and arm."
In other words, most researchers trying to make robots open doors, cabinets, and similar things rely on a simple approach: keep the robot's base in place and move its arms to perform the task. It's easier to do -- and in fact that's how most robot manipulation but limits the kinds of tasks a robot could accomplish.
The Georgia Tech researchers allow their robot to move its omni-directional base while simultaneously pulling things open -- an approach they say improves the performance of the task.
There's no better way to understand it than seeing the robot in action:
So how did they do it?
First, a look at their robot. According to Travis Deyle, a researcher at the Healthcare Robotics Lab who first reported on the new robot and its capabilities at Hizook, the robot is called Cody [photo, right]. It consists of a Segway RMP 50 Omni base with Mecanum wheels, a vertical linear actuator to raise the robot's torso up to 1.2 meter above the ground, a laser range finder, and a pair of 7-DOF MEKA Robotics arms.
A Mac Mini running Linux performs all the computation for the sensing and high-level control. Another computer running a Linux-based real time system controls the MEKA arms. The researchers wrote all their software in Python and used open source packages like ROBOOP and ROS.
The robot uses a simple hook as its end effector, which the researchers built with a 3D printer and coated with rubber to increase friction. At the wrist, a 6-axis force sensor measures the forces on the hook, which was based the way a person uses a finger to pull something open [photo below].
But the most innovative thing is the control method they implemented, which they call equilibrium point control, or EPC. Here's the gist. Rather than model the dynamics of the arm and the impedance at the end effector or use inverse dynamics, the researchers created a control system that relies on simulated visco-elastic springs at the robot's joints. The EPC system uses these virtual springs, whose stiffness can be adjusted, to determine how the joints should move to achieve a desired movement.
Kemp and Jain say that this approach, combined with the robot's low mechanical impedance (which reduces the forces resulting from contact and thus minimizes the risks of damage to the robot, objects, and people), proved "easy to work with, easy to implement, and surprisingly effective."
They tested their approach with 10 different doors and drawers, reporting that the robot succeeded in 37 out of 40 trials. What's more, the robot was able to open doors and drawers from initial positions that would be difficult for static robots to succeed at the task.
They write: "We empirically demonstrate that the system is robust to common forms of task variation, including variation in the mechanism being operated (tested with 7 doors and 3 drawers), and variation in the pose of the robot's base with respect to the handle."
I think that's researchspeak for "It works!"
Images and video: Georgia Tech's Healthcare Robotics Lab
This is the microrobotics competition arena. Image: NIST
At the IEEE International Conference on Robotics and Automation, in Anchorage, Alaska, this week, the U.S. National Institute of Standards and Technology, the famed NIST, is holding a robotics competition for small robots -- very small robots.
In the Mobile Microrobotics Challenge, robots with dimensions measured in micrometers will square off in a series of challenges taking place at a, uh, microchip playing field [photo above]. First there's a race across a 2 millimeter distance, or the equivalent to the diameter of a pin head. Then the microbots will compete in a microassembly challenge in which they'll have to insert tiny pegs into tiny holes. Finally, there's a freestyle competition in which each team chooses how to show off its small bot in a grand way.
Researchers will remote operate the microrobots, viewed under a microscope, using magnetic fields or electrical signals transmitted across . The bots, made from materials like silicon, gold, aluminum, nickel, and chromium, are a few tens of micrometers to a few hundred micrometers across and weigh just a few nanograms.
As the organizers put it, "These events are designed to 'road test' agility, maneuverability, response to computer control and the ability to move objects—all skills that future industrial microbots will need for tasks such as microsurgery within the human body or the manufacture of tiny components for microscopic electronic devices."
Here's a schematic of the 2 millimeter racetrack:
And here are the contenders:
Team Name: Magic & Voodoo
Organization: Carnegie Mellon University (Pittsburgh, Pennsylvania)
Robot Dimensions: Under 500 micrometers in all dimensions
Materials: Neodymim-Iron-Boron magnetic particles suspended in a polyurethane matrix material
MagPieR (Magnetic - Piezoelectric microRobot)
Team Name: CNRS Team (The French Team)
Organization: FETO-ST Institute; ISIR - Institut des Systemes Intelligents et de Robotique (France)
Robot Dimensions: Under 400 micrometers in all dimensions
Materials: The MagPieR microrobotis composed of two distinct layers, an upper using a ferromagnetic metal (such as nickel) and a lower using a piezoelectric material.
Team Name: MagMite Team
Organization: ETH Zurich (Switzerland)
Robot Dimensions: Under 300 micrometers in all dimensions
Materials: The device consists of two nickel masses connected through a gold spring.
µMAB (Micro-scale Magnetostrictive Asymmetric thin-film Bimorph)
Team Name: Stevens Institute of Technology
Organization: Stevens Institute of Technology (Hoboken, New Jersey)
Robot Dimensions: Under 600 micrometers in all dimensions
Materials: Nickel, copper
Team Name: University of Maryland
Organization: University of Maryland (College Park, Maryland)
Robot Dimensions: 500 micrometers in all dimensions
Materials: The device is silicon cube with a layer of nitride on the top surface, and platium on the bottom
EMMA (ElectroMagnetic Microrobotic Actuation)
Team Name: University of Waterloo Nanorobotics Group
Organization: University of Waterloo (Canada)
Robot Dimensions: 500 micrometers and under in all dimensions
Materials: Nickel, cobalt, manganese, phosphorus
Team Name: U.S. Naval Academy Microrobotics Team
Organization: U.S. Naval Academy (Annapolis, Maryland)
Robot Dimensions: 300 micrometers in diameter
Materials: Nickel, gold, polysilicon, nitride
We'll keep you updated about the competition and winners, and try to get some video as well.
UC Berkeley researchers demonstrated a PR2 robot that could fold towels. Image: UC Berkeley
Watch out, towels of the world, more PR2 robots are coming for you.
Willow Garage, the Silicon Valley company dedicated to advancing open robotics, is announcing this morning that it will award 11 PR2 robots to institutions and universities around the world as part of its efforts to speed-up research and development in personal robotics.
The company, in Menlo Park, Calif., hopes that the 11 organizations [see list below] in the United States, Europe, and Japan that are receiving PR2 robots at no cost—a total worth over US $4 million—will use the robots to explore new applications and contribute back to the open-source robotics community.
An open robot platform design and built by Willow, the Personal Robot 2, or PR2, has a mobile base, two arms, a variety of sensors, and 16 CPU cores for computation. But what makes the robot stand out is its software: the open-source Robot Operating System, or ROS, that offers full control of the PR2, including libraries for navigation, manipulation, and perception.
Yesterday I spoke with Eric Berger, Willow's co-director of the personal robotics platform program, who said they’re "really excited about the new applications that will come out of this."
As an example of the possibilities, he mentioned that earlier this year a group at UC Berkeley programmed a PR2 to fold towels. The video of the robot neatly folding a stack of towels went viral.
"People get very excited with the idea of robots doing something that's really useful in their homes," Berger says. "People have seen a lot of military robots, industrial robots, robot vacuum cleaners, but the idea of something like Rosie the Robot, I think it's very powerful."
With its PR2 Beta Program, Willow Garage hopes to foster scientific robotics research, promote the development of new tools to improve the PR2 and other robots, and also help researchers create practical demonstrations and applications of personal robotics.
For the researchers receiving a state-of-the-art personal robot platform worth several hundred thousand dollars, the possibility of working on real-world problems without having to waste time reinventing the robotic wheel, so to speak, is a big deal.
Even more significant, the researchers will be able to "share their software for use by other groups and build on top of each other's work," says Pieter Abbeel, the UC Berkeley professor who created the towel folding demo and is one of the PR2 recipients. "This will significantly boost the rate of progress in robotics, and personal robotics in particular."
"Just as the Mac and PC hardware inspired new applications for personal computers in the 1980s, the PR2 could be the key step in making personal robots a reality," says Ken Goldberg, an IEEE Fellow and UC Berkeley professor. "It's a very exciting step forward for robotics and we're very excited to participate."
The PR2 robot is an advanced mobile and manipulation platform. Image: Willow Garage
Eric Berger told me that one of the PR2 Beta Program's main goals -- and of Willow itself -- is improving the software side of robotics. Today a lot of research groups write their own code, wasting time creating tools that already exist. Willow aims to address that with its ROS, an open-source framework that robotic developers can use and share.
“I think there’s definitely hardware problems to solve, but a lot of the biggest problems that we’re facing right now have to do with software and applications," Berger says. "That's what we're trying to enable with this [program]."
Berger compares the evolution of robotics to that of computers. Robotics is going from something designed to solve a specific problem to something that is a general-purpose system, he says.
"Once robots have reached a certain level of capability, then it's a question of what do you make them do."
Willow says the ROS software is BSD-licensed, making it completely free for anyone to use and change, and free for companies to commercialize on. The company hopes advances in personal robotics could have an impact in a wide range of industries, including retail, health care, home care, automotive, and manufacturing.
Willow had announced the PR2 Beta Program early this year, inviting research groups to submit proposals showing how they'd use a PR2. Willow received 78 proposals from all over the world and selected 10—adding an 11th recipient at the last minute. The selected proposals include three in Europe and one in Japan.
In selecting the 11 PR2 recipients, Berger said they wanted diversity in terms of applications, but at the same time they focused on those that could make the best use of PR2's mobility and manipulation capabilities. The selected institutions will pursue their research and development goals and regularly meet to share their progress and explore new applications together.
Here's the list of lucky 11 PR2 recipients that Willow is releasing this morning:
* Albert-Ludwigs-Universität Freiburg with the proposal TidyUpRobot
The University of Freiburg's strength in mapping has led to multipleopen-source libraries in wide use. Their group will program the PR2 to do tidy-up tasks like clearing a table, while working on difficult underlying capabilities, like understanding how drawers and refrigerators open, how to recognize different types of objects, and how to integrate this information with the robot's map. Their goal is to detect, grasp, and put away objects with very high reliability, and reproduce these results at other PR2 Beta Program sites.
* Bosch with the proposal Developing the Personal Robotics Market: Enabling New Applications Through Novel Sensors and Shared Autonomy Bosch will bring their expertise in manufacturing, sensing technologies and consumer products. Bosch will be making robotic sensors available to members of the PR2 Beta Program, including a limited number of "skins" that will give the PR2 the ability to feel its environment. Bosch will also make their PR2 remotely accessible and will expand on the libraries they've released for ROS.
* Georgia Institute of Technology with the proposal Assistive Mobile Manipulation for Older Adults at Home
The Healthcare Robotics Lab at Georgia Tech will be placing the PR2 in an "Aware Home" to study how robots can help with homecare and creative assistive capabilities for older adults. Their research includes creating easierways for adults to interact with robots, and enabling robots to interact with everyday objects like drawers, lamps, and light switches. Their human-robot interaction focus will help ensure that the software development is closely connected to real-world needs.
* Katholieke Universiteit Leuven with the proposal Unified Framework for Task Specification, Control and Coordination for Mobile Manipulation KU Leuven in Belgium is a key player in the open-source robotics community. As one of the founding institutions for the Orocos Project, they will be improving the tools and libraries used to program robots in ROS, by, for example, integrating ROS with Blender. They will also be working on getting the PR2 and people to perform tasks together, like carrying objects through a crowded environment.
* MIT CSAIL with the proposal Mobile Manipulation in Human-Centered Environments
The diverse MIT CSAIL group will use the PR2 to study the key capabilities needed by robots that operate in human-centered environments, such as safe navigation, interaction with humans via natural language, object recognition, and planning for complex goals. Their work will allow robots to build the maps they need in order to move around in buildings as large as MIT’s 11-story Stata Center. They will also program the PR2 to put away groceries and do simple cleaning tasks.
* Stanford University with the proposal STAIR on PR2 PR1 was developed in Kenneth Salisbury's lab at Stanford, and ROS was developed from the STAIR (Stanford AI Robot) Project. We're very excited that the PR2 will become the new platform for the STAIR Project's innovative research. Their team will work on several applications, which include taking inventory, retrieving items scattered about a building, and clearing a table after a meal.
* Technische Universität München with the proposal CRAM: Cognitive Robot Abstract Machine TUM will research giving the PR2 the artificial intelligence skills and 3D perception to reason about what it is doing while it performs various kitchen tasks. These combined improvements will help the PR2 perform more complicated tasks like setting a table, emptying a dishwasher, preparing meals, and other kitchen-related tasks.
* University of California, Berkeley with the proposal PR2 Beta Program: A Platform for Personal Robotics
The PR2 is now known as the "Towel-Folding Robot", thanks to the impressive efforts of Pieter Abbeel's lab at Berkeley. In two short months, they were able to get the PR2 to fold fifty towels in a row. Berkeley will tackle the much more difficult challenge of doing laundry, from dirty laundry piles to neatly folded clothes. In addition, their team is interested in hierarchical planning, object recognition, and assembly and manufacturing tasks (e.g. IKEA products) through learning by demonstration
* University of Pennsylvania with the proposal PR2GRASP: From Perception and Reasoning to Grasping
The GRASP Lab proposal aims to tackle some of the challenges facing household robotics. These challenges include tracking people and planning for navigation in dynamic environments, and transferring handheld objects between robots and humans. Their contributions will include giving PR2 a tool belt to change its gripper on the fly, helping it track and navigate around people, and performing difficult two-arm tasks like opening spring-loaded doors.
* University of Southern California with the proposal Persistent and Persuasive Personal Robots (P^3R): Towards Networked, Mobile, Assistive Robotics USC has already demonstrated teaching the PR2 basic motor skills so that it can adapt to different situations and tasks, such as pouring a cup. They will continue to expand on this work in imitation learning and building and refining skill libraries, while also doing research in human-robot interaction and self-calibration for sensors.
* University of Tokyo, Jouhou System Kougaku (JSK) Laboratory with the proposal Autonomous Motion Planning for Daily Tasks in Human Environments using Collaborating Robots
The JSK Laboratory at the University of Tokyo is one of the top humanoid robotics labs in the world. Their goal is to see robots safely and autonomously perform daily, human-like tasks such as retrieving objects and cleaning up domestic environments. They'll also be working on getting the PR2 to work together with other robots, as well as integrating the ROS, EusLisp, and OpenRAVE frameworks.
And here's a video describing the PR2 Beta Program: