RoboChamps

Microsoft have recently launched the RoboChamps simulation robotics competition and portal.

The Robochamps.com portal supports the league competitions with training, access to software, and community features. Robochamps is based on simulation, therefore you don't need any real robotics hardware in order to compete. The idea is that you can start programming robots simply using the Microsoft Developer Studio 2008 and Visual Studio.

As the competition is based on MRDS 2008 and its simulation capabilities you can use any .NET language to program your simulated robot. The good thing is that you could use exactly the same code to control a real physical robot. Anyhow, the great advantage of this software simulated competition is that you are provided with rich simulation environments. Usually, it is really hard to build an scenario like that in the real world, so using these simulation environment allow us to test and train our robot controllers in nearly real world situations. Imagine controlling your rescue robot in a city that has just suffer a natural dissaster or a terrorist attack, or let your autonomous car drive under intense traffic conditions... or the much more relaxing exploration of the surface of Mars. These are some of the challenges proposed in RoboChamps.

Each challenge consist of a 3D simulation environment, a robots, a chanllenge scenario, and a set of rules for completing the scenario. Also, a referee service will monitor your control service, ensuring that the rules are followed, and determining your score and submitting it to RoboChamps.com.

The available RoboChamp challenges are:

• AMAZED CHALLENGE:  Use your sensors to avoid traps and other surprises as you navigate the twists and turns of Amazed.
  
  

• MARS ROVER: CHALLENGE: Next Stop, Mars! Navigate the terrain of the red planet and collect data for analysis back on Earth.
  
  
• URBAN CHALLENGE: Do you hate driving downtown? What if you could program a car to do the driving itself? Now you can.
  
  
• SEARCH & RESCUE CHALLENGE: Ready to be a hero? Scour thought the post-disaster rubble to find and rescue survivors in this challenge.
  
  
• SUMO CHALLENGE: Two robots. One ring. It's sumo time! Outmaneuver your opponent and push it out of the ring to reign victorious.
  
  
• TOURNAMENT: Are you the best of the best? Take to the field with your robot and your best code to compete head to head against fellow leaguers.
  
  

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First of all, the mirror test is not exactly intended as a general test for consciousness, but a specific test for self-consciousness, and more exactly self-recognition. It is generally applied to some higher mammals and infants. The test consists on determining whether or not the subject can recognize its own reflection in a mirror. So far, only subjects belonging to the following species have passed the mirror test:

Mirror Test

humans (over 2 years old),
great apes (bonobos, chimps, orangutans, and gorillas),
rhesus monkeys,
elephants,
bottlenose dolphins,
rats,
and octopuses.

I think it is important to note that only a determined number of individuals of these species have passed the tests, while others generally fail to pass it. Obviously the test has to be adapted to each specie, although it typically consists on an odorless paint mark made in the forehead while the animal is anesthetized.

The mirror test has been considered by some researchers as one of the best available ways to test self-consciousness in organisms (see for instance how it is applied to Elephants in [1], and see [2] for an open discussion about the mirror test validity). Mirror test is famous thanks to its application to primates, as introduced by Gordon Gallup in the 70’s [3]. However, little work has been done in the application of the mirror test to robots.

Can we build a robot able to successfully pass the mirror test? And if so, does it really mean that the robot is self-aware?

Robot Mirror Test

Takeno et al. [4] at Meiji University in Japan claim that they have succeeded in achieving mirror image cognition for a robot. They define four steps for their experiments, where four robots are used: the self robot Rs, the other robot Ro, the controlled robot Rc, and the automatic robot Ra. The first two robots are endowed with the mirror image cognition system. The third robot is controlled by the self robot, while the last one moves automatically.

The four experiments are as follows:

1) The self robot Rs imitates the action of its own image reflected in a mirror.
2) The self robot Rs imitates an action taken intentionally by the other robot Ro as imitative behavior.
3) The controlled robot Rc is controlled completely from the self-robot to imitate his behavior.
4) The self robot Rs imitates the random actions of the automatic robot Ra.

The robot is able to recognize its own image reflected in a mirror without confusing it with the image of another robot with the same physical aspect. The mirror image cognition system is based on an artificial neural network. The aim of this system is to recognize and differentiate robot’s own behavior from other robot’s behavior. Takeno also suggests that imitation is a proof of consciousness as it requires the recognition of other subject’s behavior and then the application of that behavior to oneself.

The results described in the paper indicate that in some way the robots are passing the mirror test with an accuracy of 70%, but I am reluctant to claim that they are self-conscious. I would rather say that the present a-consciousness of their recognized image.

[1] http://www.conscious-robots.com/en/neuroscience/mammals-brain/elephants-recognize-themselves-in-the-m-3.html
[2] http://www.conscious-robots.com/en/forums-./test-for-consciousness/mirror-test/view.html
[3] Gallup, G.G., Jr. (1977). Self-recognition in primates: A comparative approach to the bidirectional properties of consciousness. American Psychologist, 32, 329-337.
[4] Junichi Takeno, Keita Inaba, Tohru Suzuki. Experiments and examination of mirror image cognition using a small robot. Proceedings. 2005 IEEE International Symposium on Computational Intelligence in Robotics and Automation, 2005. CIRA 2005. Full paper available at: http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=1554325

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