iRobis Announces Complete Cognitive Software System for Robots

Institute of Robotics in Scandinavia (iRobis) has announced that the world’s first “complete cognitive software system for robotics” is ready for application. The system turns robots into self-developing, adaptive, problem-solving, “thinking” machines. http://mensnewsdaily.com/2007/05/16/robobusiness-robots-with-imagination/

Brainstorm automatically adapts to onboard sensors and actuators, immediately builds a model of any robot on which it is installed, and automatically writes control programs for the robot’s movements. It can then explore and model its environment. Through simulated interaction using these models, it solves problems and develops new behavior using “imagination.” Once it has “learned” to do something, it can use its imagination to adapt its behavior to a wide range of circumstances.

A methodology known as genetic programming (GP) is “the trick” that makes it all possible. GP is an automated programming methodology inspired by natural evolution that is used to evolve computer programs. Evolving computer programs means the logic developed by the system can be anything that can be expressed by a computer program. That basically means anything. Robots need descriptions of things they are supposed to do and they figure out how to do them. GP itself is not an approach exclusive to robotic behavior. It has been applied to a variety of problems, some already yielding commercial successes. An example well-known to scientists in the field was the development of invention machines that had created two new patentable inventions by 2002. The potential for “thinking robots” goes well beyond developing their own actions.

The system is constructed using components and the learning / adaptive mechanisms can be turned on and off. This provides a broad range of choices to satisfy requirements. It can for example, be used for rapid development of control systems that cannot be modified after testing is complete or the learning adaptive system can remain on during use allowing the robot to continue to evolve as it gains real-life experience. The level of learning and adaptation can be adjusted to requirements. It can be used to build robot software from the ground up fulfilling all requirements or an add-on to an existing system that provides learning and adaptive behavior. Although product development time can be significantly shortened and less costly, it will still follow a familiar pattern. Product developers need to define their product requirements and engineers will make decisions about the best configurations and settings.

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