Blog: Finding ET May Require Giant Robotic Leap

Finding ET May Require Giant Robotic Leap
Penn State Live (04/18/12) Andrea Elyse Messer

Autonomous, self-replicating robots, known as exobots, are the best way to explore the universe, find and identify extraterrestrial life, and clean up space debris, says Pennsylvania State University professor John D. Mathews. "The basic premise is that human space exploration must be highly efficient, cost effective, and autonomous, as placing humans beyond low Earth orbit is fraught with political, economic, and technical difficulties," Mathews says. Developing and deploying self-replicating robots and advanced communications systems is the only way humans can effectively explore the asteroid belt and beyond, he maintains. The initial robots could be manufactured on the moon, taking advantage of the resources and its low gravity, both of which would reduce costs. The robots must be able to identify their exact location and the location of the other exobots, which would enable them to communicate using an infrared laser beam carrying data. Initially, the exobots would clear existing debris and monitor the more than 1,200 near-Earth asteroids that could be dangerous. In the future, he says a network of exobots could spread throughout the solar system and into the galaxy, using the resources they find there to continue their mission.

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Blog: Self-Sculpting Sand

Self-Sculpting Sand
MIT News (04/02/12) Larry Hardesty

Massachusetts Institute of Technology (MIT) researchers are developing a type of reconfigurable robotic system called smart sand. The individual sand grains pass messages back and forth and selectively attach to each other to form a three-dimensional object. MIT professor Daniela Rus says the biggest challenge in developing the smart sand algorithm is that the individual grains have very few computational resources. The grains first pass messages to each other to determine which have missing neighbors. Those with missing neighbors are either on the perimeter of the pile or the perimeter of the embedded shape. Once the grains surrounding the embedded shape identify themselves, they pass messages to other grains a fixed distance away. When the perimeter of the duplicate is established, the grains outside it can disconnect from their neighbors. The researchers built cubes, or “smart pebbles,” to test their algorithm. The cubes have four faces studded with electropermanent magnets, materials that can be magnetized or demagnetized with a single magnetic pulse. The grains use the magnets to connect to each other, to communicate, and to share power. Each grain also is equipped with a microprocessor that can store 32 kilobytes of code and has two kilobytes of working memory.

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Blog: Robots to Organise Themselves Like a Swarm of Insects

Robots to Organise Themselves Like a Swarm of Insects
The Engineer (United Kingdom) (03/26/12)

A swarm of insects is the inspiration for a warehouse transport system that makes use of autonomous robotic vehicles. Researchers at the Fraunhofer Institute for Material Flow and Logistics (IML) have developed autonomous Multishuttle Moves vehicles to organize themselves like insects. The team is testing 50 shuttles at a replica warehouse. When an order is received, the shuttles communicate with one another via a wireless Internet connection and the closest free vehicle takes over and completes the task. "We rely on agent-based software and use ant algorithms based on the work of [swarm robotics expert] Marco Dorigo," says IML's Thomas Albrecht. The vehicles move around using a hybrid sensor concept based on radio signals, distance and acceleration sensors, and laser sensors to calculate the shortest route to any destination and avoid collisions. Albrecht says the system is more flexible and scalable because it can be easily adapted for smaller or larger areas based on changes in demand. "In the future, transport systems should be able to perform all of these tasks autonomously, from removal from storage at the shelf to delivery to a picking station," says IML professor Michael ten Hompel.

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Blog: Smart Swarms of Bacteria Inspire Robotics Researchers

Smart Swarms of Bacteria Inspire Robotics Researchers
American Friends of Tel Aviv University (11/17/11)

Tel Aviv University (TAU) researchers have developed a computational model that describes how bacteria move in a swarm, a discovery they say could be applied to computers, artificial intelligence, and robotics. The model shows how bacteria collectively gather information about their environment and find an optimal plan for growth. The research could enable scientists to design smart robots that can form intelligent swarms, help in the development of medical micro-robots, or de-code social network systems to find information on consumer preferences. "When an individual bacterium finds a more beneficial path, it pays less attention to the signals from the other cells, [and] since each of the cells adopts the same strategy, the group as a whole is able to find an optimal trajectory in an extremely complex terrain," says TAU Ph.D. student Adi Shklarsh. The model shows how a swarm can perform optimally with only simple computational abilities and short term memory, Shklarsh says. He notes that understanding the secrets of bacteria swarms can provide crucial hints toward the design of robots that are programmed to perform adjustable interactions without needing as much data or memory.

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Blog: Squishybots: Soft, Bendy and Smarter Than Ever

Squishybots: Soft, Bendy and Smarter Than Ever
New Scientist (11/16/11) Justin Mullins

A squishy, tentacled configuration may be an accurate design model for future robots, as a rigid humanoid shape is proving impractical for many of the tasks people want robots to perform. A key element of such designs is morphological computing, a discipline that holds that a robot's intelligence can be enhanced through the optimization of its body's interaction with its environment. This represents an inversion of conventional thinking, which dictates that an organism has a central processing capability where intelligence in housed, and its body's interaction with its surroundings demonstrates that intelligence. Using the embodied intelligence approach, researchers in Pisa, Italy, are building a soft, rubbery robot octopus equipped with appendages whose grasping ability exceeds that of the most advanced robots. Another speculative application of morphological computing principles is a soft robot surgeon concept that Kings College London researchers are studying. The robot would enter the body through a natural orifice or incision, pass soft tissues and organs without impediment, and harden once in place. The advantage of the embodied intelligence strategy is that the robots will be ideally suited for the job at hand.

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Blog: Robotics Team Finds Artificial Fingerprints Improve Tactile Abilities

Robotics Team Finds Artificial Fingerprints Improve Tactile Abilities
PhysOrg.com (09/21/11) Bob Yirka

National University of Singapore researchers have demonstrated how adding artificial fingerprints to robot fingers can increase tactile sensation, enabling the robot to discern the differences in the curvature of objects. The researchers, led by Saba Salehi, John-John Cabibihan, and Shuzhi Sam Ge, built a touch sensor consisting of a base plate, embedded sensors, and a raised ridged surface. The researchers tested the sensor in a variety ways to determine if they were able to use it to sense things in different ways, specifically as it was applied to flat, edged, and curved objects. The researchers found that the raised sensor provided more feedback information than the one with the flat surface, so much so that they were able to tell the difference in the three types of objects with 95.7 percent accuracy.

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Blog: Robot 'Mission Impossible' Wins Video Prize

Robot 'Mission Impossible' Wins Video Prize
New Scientist (08/12/11) Melissae Fellet

Free University of Brussels researchers have developed Swarmanoid, a team of flying, rolling, and climbing robots that can work together to find and grab a book from a high shelf. The robot team includes flying eye-bots, rolling foot-bots, and hand-bots that can fire a grappling hook-like device up to the ceiling and climb the bookshelf. Footage of the team in action recently won the video competition at the Conference on Artificial Intelligence. The robotic team currently consists of 30 foot-bots, 10 eye-bots, and eight hand-bots. The eye-robots explore the rooms, searching for the target. After an eye-bot sees the target, it signals the foot-bots, which roll to the site, carrying the hand-bots. The hand-bots then launch the grappling hooks to the ceiling and climb the bookshelves. All of the bots have light-emitting diodes that flash different colors, enabling them to communicate with each other. Constant communication enables Swarmanoid to adjust its actions on the fly, compensating for broken bots by reassigning tasks throughout the team.

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Blog: Crowdsourced Online Learning Gives Robots Human Skills

Crowdsourced Online Learning Gives Robots Human Skills
New Scientist (07/26/11) Jim Giles

Roboticists are experimenting with using crowdsourcing to teach robots more general skills. By allowing users to pilot real or simulated robots over the Internet in trial experiments, the researchers hope to create machines that can simulate a human's flexibility and dexterity. "Crowdsourcing is a really viable path toward getting robots to do things that are useful for people," says Brown University's Chad Jenkins. Crowdsourcing also can be used to develop better human-robot interactions, says Worcester Polytechnic Institute's Sonia Chernova. She has led a team that developed Mars Escape, an online game in which two users each control an avatar, one human and one robot, to collect information on teamwork, social interaction, and communication. After more than 550 game sessions, the researchers looked for patterns in the data, such as methods that players frequently used to retrieve objects, and phrases they exchanged when doing so. The researchers then set up a mock real-life version of the game in which visitors were paired with a robot powered by software based on the Mars Escape data. During testing, most of the visitors said the robot behaved rationally and contributed to the team's success.

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Blog: Automaton, Know Thyself: Robots Become Self-Aware

Automaton, Know Thyself: Robots Become Self-Aware
Scientific American (02/24/11) Charles Q. Choi

Cornell University's Hod Lipson is developing robots that can reflect on their own thoughts by equipping them with two controllers. One controller was rewarded for chasing dots of blue light while avoiding red dots, and the second controller modeled how the first behaved and how successful it was. This technique, known as metacognition, enabled the robot to adapt after about 10 physical experiments, as opposed to the thousands of experiments needed using traditional evolutionary robots. "This could lead to a way to identify dangerous situations, learning from them without having to physically go through them--that's something that's been missing in robotics," says University of Vermont's Josh Bongard. Lipson also is studying how robots can model what others are thinking by programming one robot to watch another randomly move toward a light. The observer developed the ability to predict the other's movements so well that it could lay a trap for it on the ground. "This research might also shed new light on the very difficult topic of our self-awareness from a new angle--how it works, why, and how it developed," Lipson says. One application for self-aware robots could be the maintenance of a bridge, with sensors constantly monitoring vibrations in the framework to develop a self-image of the bridge.

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Blog: Cloud Robotics: Connected to the Cloud, Robots Get Smarter

Cloud Robotics: Connected to the Cloud, Robots Get Smarter
IEEE Spectrum (01/24/11) Erico Guizzo

Carnegie Mellon University (CMU) researchers are developing robots that use cloud computing to obtain new information and data. The method, known as cloud robotics, allows robots to offload compute-intensive tasks such as image processing and voice recognition. Cloud robotics could lead to lighter, cheaper, and faster robots, says CMU professor James Kuffner. He is working with Google to develop cloud robotics systems that involve "small mobile devices as Net-enabled brains for robots." In the future, cloud-enabled robots could become standardized, leading to an app store for robots, Kuffner says. "Coupling robotics and distributed computing could bring about big changes in robot autonomy," says Jean-Paul Laumond with France's Laboratory of Analysis and Architecture of Systems. Kuffner sees a future in which robots will feed data into a knowledge database, sharing their interactions with the world and learning about new objects, places, and behaviors.

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Blog: Rats to Robots--Brain's Grid Cells Tell Us How We Navigate

Rats to Robots--Brain's Grid Cells Tell Us How We Navigate
Queensland University of Technology (11/12/10) Niki Widdowson

Queensland University of Technology (QUT) robotics researchers have formulated a theory on how the brain combines separate pieces of information to map out familiar environments and navigate them. The theory was prompted by practical improvements that were made to the navigation system of robots that were having problems with some navigational tasks. QUT's Michael Milford says that Norwegian researchers recently discovered new cells in the brains of rats that are arranged in a grid and fire every time a rat is in one of a number of locations. Preliminary evidence also suggests that other animals, including humans, have certain cells that fire only when they are in a certain place. A person who may not be paying attention when exiting an elevator would begin to think he or she is on the second floor when seeing a Coke machine and then a photocopier. "We are postulating that the 'grid cells' help put these two pieces of information together to tell you you're on the second floor," Milford says. "In this study we are able to enhance our understanding of the brain by providing insights into how the brain might solve a common problem faced by both mobile robots and animals."

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Blog: The Ethical Robot

The Ethical Robot
University of Connecticut (11/08/10) Christine Buckley; Bret Eckhardt

University of Connecticut professor Susan Anderson and University of Hartford computer scientist Michael Anderson have programmed a robot to behave ethically. Their work is part of a relatively new field of research known as machine ethics. "There are machines out there that are already doing things that have ethical import, such as automatic cash withdrawal machines, and many others in the development stages, such as cars that can drive themselves and eldercare robots," says Susan Anderson. Machine ethics combines artificial intelligence with ethical theory to determine how to program machines to behave ethically. The robot, called Nao, is programmed with an ethical principle that determines how often to remind people to take their medicine and when to notify a doctor when they do not comply. "We should think about the things that robots could do for us if they had ethics inside them," says Michael Anderson. Interacting with robots that have been programmed to behave ethically could inspire humans to behave more ethically, says Susan Anderson.

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Blog: Part Moth, Part Machine: Cyborgs Are on the Move

Part Moth, Part Machine: Cyborgs Are on the Move
New Scientist (11/08/10) Duncan Graham-Rowe

Researchers are developing methods to produce complex behavior from robots by tapping into the nervous system of living organisms and using algorithms that already exist in nature. For example, Tokyo Institute of Technology researchers have developed a cyborg moth that uses chemical plume tracking to locate the source of certain pheromones. The researchers immobilized a moth on a small wheeled robot and placed two recording electrodes into nerves running down its neck to monitor commands the moth uses to steer. By rerouting these signals to motors in the robot, the researchers found that they could emulate the moth's plume-tracking behavior. Researchers also hope to recreate biological circuits in silicon, says Northwestern University's Ferdinando Mussa-Ivaldi. Scientists have made progress toward this goal with central pattern generators (CPGs), which are a type of behavioral circuit in the human brain and spine that carry out routine tasks with little or no conscious input, such as walking or grasping an object. Johns Hopkins University's Ralph Etienne-Cummings has used recordings of CPGs taken from a lamprey to generate walking motions in a pair of robotic legs.

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Blog: Flying Robot Swarm Takes Off

Flying Robot Swarm Takes Off
Wired News (09/27/10) Olivia Solon

The Ecole Polytechnic Federale de Lausanne is experimenting with flying robots that would create a communications network for rescuers in disaster areas. Researchers involved in the Swarming Micro Air Vehicle Network project have equipped 10 flying robots with autopilot capabilities to control altitude, airspeed, and turn rate, and have designed a microcontroller that uses three sensors--a gyroscope and two pressure sensors. The robots have a global positioning system module for logging flight journeys, and the swarm controllers running Linux are connected to an off-the-shelf USB Wi-Fi dongle. Army ants serve as the inspiration for the way the flying robots lay and maintain communications pathways between a base node and users in the environment. Deployed as node micro air vehicles (MAVs), the flying robots spread out to create a grid for depositing and detecting virtual pheromone through local communication. And as ant MAVs, the robots travel along this grid until they reach an unoccupied position, which then becomes a node MAV, to extend the grid until there is a connection with the target user in the environment.

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Blog: Tiny MAVs May Someday Explore and Detect Environmental Hazards

Tiny MAVs May Someday Explore and Detect Environmental Hazards
Air Force Print News (09/14/10) Maria Callier

The next phase of high-performance micro air vehicles (MAVs) for the Air Force could involve insect-sized robots for monitoring and exploring hazardous environments. "We are developing a suite of capabilities which we hope will lead to MAVs that exceed the capabilities of existing small aircraft," says Harvard University researcher Robert Wood. His team is studying how wing design can impact performance for an insect-size, flapping-wing vehicle. The research also will shape the devices' assembly, power supply, and control systems. The team is constructing wings and moving them at high frequencies to recreate trajectories that are similar to an insect's. The researchers are able to measure multiple-force components, and monitor fluid flow around the wings flapping in excess of 100 times per second. The team also is conducting high-speed stereoscopic motion tracking, force measurements, and flow visualization to better understand these systems.

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Blog: DARPA Wants to Create Brainiac Bot Tots

DARPA Wants to Create Brainiac Bot Tots
Wired News (09/10/10) Katie Drummond

The U.S. Defense Advanced Research Projects Agency (DARPA) is funding scientist Shane Mueller's efforts to expand upon the Turing test as part of an attempt to determine the level of artificial intelligence in bot tots. DARPA is interested in developing robots with the capabilities of an average toddler. "There were many motivations for this target, but one central notion is that if one could design a system with the capabilities of a two-year-old, it might be possible to essentially grow a three-year-old, given realistic experiences in a simulated environment," Mueller says. DARPA's goal is for tot bots to become super smart by learning like a human. Mueller uses a testing schema that has categories for visual recognition, search abilities, manual control, knowledge learning, language and concept learning, and simple motor control. The artificial intelligence agents would initially operate much like a toddler, but they would gradually learn from their surroundings and an instructor, and eventually gain advanced cognitive capabilities.

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Blog: MIT Builds Swimming, Oil-Eating Robots

MIT Builds Swimming, Oil-Eating Robots
Computerworld (08/26/10) Gaudin, Sharon

Massachusetts Institute of Technology (MIT) researchers have developed a robot using nanotechnology that can autonomously navigate across an ocean's surface and clean up an oil spill. The researchers say that a fleet of 5,000 robots, called a Seaswarm, could clean up a spill the size of the recent one in the Gulf of Mexico in about a month. "Unlike traditional skimmers, Seaswarm is based on a system of small, autonomous units that behave like a swarm and 'digest' the oil locally while working around the clock without human intervention," says MIT's Carlo Ratti. Seaswarm is designed to use a conveyor belt covered with a thin nanowire mesh that absorbs oil. The nanomesh repels water while absorbing 20 times its own weight in oil. A team of robots would use wireless communications and global positioning systems to move across the ocean without bunching up or leaving some parts uncleaned.

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Blog: Riders on a Swarm

Riders on a Swarm
Economist (08/12/10)

Free University of Brussels (FUB) researchers are developing artificial intelligence systems based on ant behavior. In 1992, FUB researcher Marco Dorigo and his team developed Ant Colony Optimization (ACO), an algorithm that analyzes problems by simulating a group of ants wandering over an area and laying down pheromones. ACO has since grown into a wide family of algorithms that have been applied to various applications. For example, European distributors use a program called AntRoute, which takes about 15 minutes to produce a delivery plan for 1,200 trucks. The researchers also have developed AntNet, a routing protocol in which packets of information jump from node to node, leaving a trace that signals the "quality" of their trip as they go. The particle swarm optimization (PSO) algorithm is used for continuous problems that have a potentially infinite number of solutions. There are now about 650 tested PSO applications, including those for image and video analysis, antenna design, and medical diagnostic systems. Dorigo is currently working on the Swarmanoid project, which aims to develop a swarm of cheap, small robots that cooperate using swarm intelligence.

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Blog: Virtual Walkers Lead the Way for Robots

Virtual Walkers Lead the Way for Robots
New Scientist (08/06/10) Campbell, MacGregor

Researchers are studying ways to use simulated physics and evolution to give robots and virtual characters more realistic gaits. Simulated evolution, a process developed by NaturalMotion, begins with a population of virtual skeletons controlled by a network of virtual nerves. Each skeleton has a slightly different network, affecting its ability to walk. Those that can walk furthest are declared "most fit" and are used to spawn the next generation, in which a subset of the nerves are slightly altered. Over several generations the skeletons automatically evolve into better walkers. Meanwhile, University of British Columbia researcher Michiel van de Panne and University of Toronto researcher Martin de Lasa have developed overarching controllers, instead of animating a character by controlling each joint independently. The controllers create rules that specify how the character should behave, and the individual joints move to obey them. In the researchers' model, once the path of the swinging foot is specified by the controller, the angles between various joints in the leg and hip are automatically calculated. The researchers want to apply their work for use in humanoid robots.

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Blog: Self-Sustaining Robot Has an Artificial Gut

Self-Sustaining Robot Has an Artificial Gut
PhysOrg.com (07/20/10)

British researchers have developed an autonomous robot with an artificial stomach that enables it to fuel itself by eating and excreting. Bristol Robotics Laboratory researchers designed the robot, called Ecobot III, so that it consumes partially processed sewage, using the nutrients within the mixture for fuel and excreting the remains. The robot also drinks water to maintain power generation. The meal is processed by 24 microbial fuel cells (MFCs), which are held in a stack of two tiers in the robot's body. Undigested matter passes via a gravity feed to a central trough from which it is pumped back into the feeder tanks to be reprocessed in order to extract as much of the available energy as possible. The bacteria in the MFCs metabolize the organic mixture, producing hydrogen atoms in the process, which help produce an electric current. The robot has maintained itself unaided for up to seven days, but is so far extremely inefficient, using only one percent of the energy available within the food.

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