17 novemberi 2012
If you are a robot lover who hopes to have a mechanical friend that could save your life someday, we've got great news. On the other hand, if you're afraid of a hostile robot takeover, for you the news isn't so great.
Scientists in Japan have built a small humanoid robot that can walk on a tightrope, balancing itself by swinging its arms. Although, it's really more like sliding than walking. Anyway, the good news is that one day your friend might be able to rescue you from danger, if you happen to find yourself stuck somewhere only reachable by tightrope.
Of course, if you're one of those people who keeps a written copy of Isaac Asimov's Three Laws of Robotics just in case you need to issue a warning to an overly aggressive vacuum cleaner, this is the time to press the panic button. "And I thought making my house only accessible with tightropes would save me from the robot uprising," wrote a worried user in the comment thread.
Zie Two Robots Create Their Own Language, BBC’s Hunt for Artificial Intelligence
In a clip from the BBC Horizon documentary, “The Hunt for AI”, two robots learn how to move their own bodies by themselves, and go on to teaching each other their own language. Scientists at the Neurorobotics Research Laboratory believe that true artificial intelligence can only be achieved by allowing machines to develop and evolve like young children do. The focus of the research project is to explore how “complex grammatical systems and behaviors can emerge in populations of robotic agents.”
Experiments play out like a game where a teacher and observer interact to build a shared vocabulary from the ground up.
Dr. Luc Steels of the NRL explains how one of the robots is attempting to communicate its chosen word for a specific gesture. The “words” they invent begin as random sounds given to a specific action, object, or event. That coupling must then be successfully conveyed to a partner, which involves the observer guessing what the teacher meant. Whenever the observer correctly guesses the word’s definition, it enters into a shared vocabulary that can be used to study further complexities like grammar and tense (do this, then that).
If the project is a success, not only will robots be able to teach one another new words, but it will be possible for people to teach robots words in the same way we do infants. And the grammatical problems that often stump computers in Turing tests may be solved.
Zie AI vs. AI: Two chatbots talking to each other
The system depicted was created by combining three components: a chatbot, atext-to-speech synthesizer, and an avatar renderer.
Chatbots are machines designed to emulate the conversational abilities of humans, conversing with a human user and generally attempting to convince the user into thinking that the machine is human. In such a scenario, if a sufficiently adept human on one end is fooled into thinking the machine is another human, the machine would be credited as passing the famous Turing Test for intelligence. Over 60 years after its proposal by Alan Turing, there are arguably still no machines capable of passing this test. The chatbot we initially used was Eliza, a prominent early milestone from AI's infancy in the 1960's. This tended to produce fairly boring conversations, so we switched to a much smarter, constantly learning chatbot: Cleverbot. Publicly available on Cleverbot.com, this state of the art chat engine was created by AI researcher Rollo Carpenter, who can be contacted via his company, Existor. Cleverbot will continue to learn, and Existor are soon to add new capabilities aiming at a Turing Test pass sooner than you might expect.
The second piece of the system is the text-to-speech synthesizer, which takes the text generated by the chatbot and creates a spoken, audio version. There are many services able to accomplish this; we chose Acapela because it was easy to use and sounded decent.
The final piece is the avatar renderer, which synthesizes an animated character whose gestures and lips are synced to the sound stream. For this we used Living Actor Presenter.
We tied these three components together in Python, producing a single machine (one of the two screens) that can converse with a user. We then plugged the output of one machine into the input of a second, and the output of the second back into the first, producing endless comic robotic entertainment.
23 juni 2012
Zie http://www.techunited.nl/nl/nieuws/151
Eindelijk is het gelukt! EIN-DE-LIJK! In de vijfde finale op rij heeft Tech United zich beloond met de WERELDTITEL robotvoetbal in de Middle Size League!
In een spannende replay van de RoboCup Dutch Open finale werd tegen MRL uit Iran gewonnen met 4-1.
Het is niet voor te stellen hoe lang we naar dit moment uitgekeken hebben. Teamleden vallen elkaar in de armen en hier en daar zien we ogen vochtig worden. Alle avonduren, al het nachtwerk, het testen van TURTLEs in hotelkamers, vandaag betaalt het zich eindelijk uit!
Zoals gebruikelijk werd er vlak voor de wedstrijd nog veel veranderd aan de software. Het machteloze gevoel na het uploaden van de software, was deze keer sterker dan ooit. Beelden van de voorgaande vier finalewedstrijden flitsten door de hoofden van ieder teamlid. Het zou toch niet weer mis gaan in de laatste wedstrijd van het toernooi?
Tijdens de finale bleek opnieuw dat Tech United de nieuwe passingsregel, waarbij over de middellijn gespeeld moet worden, het beste beheerst. Zodoende werd er vlijmscherp gepast en ontstonden veel kansen. Daarnaast werd, geheel in Mexicaanse stijl, de Sombrero geïntroduceerd: een vlakke plaat bovenop de TURTLES die ervoor moet zorgen dat de veldspelers meer lobballen tegenhouden!
De teamleden werkend aan de AMIGO en de Humanoid robot waren minstens zo gespannen, waardoor een heuse finale-sfeer gecreëerd werd. Met een halve-finale plek voor de TUlip en een zevende plaats voor de @Homerobot mochten zij tevreden terugkijken op dit toernooi.
RoboCup - Robot Soccer Simulation - Robot Voetbal Simulatie
RoboCup2011 Instanbul Soccer Simulation 2D League Final Match
WrightEagle (University of Science and Technology of China, China)
vs.
HELIOS2011 (Fukuoka University, Osaka Prefecture University, AIST, Japan)
League Overview
Without the neccessity to maintain any robot hardware, the RoboCup Simulation League's focus comprises artificial intelligence and team strategy.
In the 2D Simulation League, two teams of eleven autonomous software programs (called agents) each play soccer in a two-dimensional virtual soccer stadium represented by a central server, called SoccerServer. This server knows everything about the game, i.e. the current position of all players and the ball, the physics and so on. The game further relies on the communication between the server and each agent. On the one hand each player receives relative and noisy input of his virtual sensors (visual, acustic and physical) and may on the other hand perform some basic commands (like dashing, turning or kicking) in order to influence its environment.
The big challenge in the Simulation League is to conclude from all possible world states (derived from the sensor input by calculating a sight on the world as absolute and noise-free as possible) to the best possible action to execute. As a game is divided into 6000 cycles this task has to be accomplished in time slot of 100 ms (the length of each cycle).
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