Autonomous Robotic Systems

The concept of fusion of soft computing and hard computing has rapidly gained importance over the last few years. Soft computing is known as a complementary set of techniques such as neural networks, fuzzy systems, or evolutionary computation which are able to deal with uncertainty, partial truth, and imprecision. Hard computing, i.e., the huge set of traditional techniques, is usually seen as the antipode of soft computing. Fusion of soft and hard computing techniques aims at exploiting the particular advantages of both realms. This article introduces a multi-dimensional categorization scheme for fusion techniques and applies it by analyzing several fusion techniques where the soft computing part is realized by a neural network. The categorization scheme facilitates the discussion of advantages or drawbacks of certain fusion approaches, thus supporting the development of novel fusion techniques and applications.

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Autonomous Robotic Systems

Abstract: Parts of this thesis are based on work described in the following publications, that appeared in refereed journals and conference proceedings, and which I completed while I was a Doctor of Philosophy student:

Cited by 2 publications

References 17 publications

Emergent Reasoning from Coordination of Perception and Action: An Example Taken from Robotics

Emergent Reasoning from Coordination of Perception and Action: An Example Taken from Robotics

Fusion of soft and hard computing: multi-dimensional categorization of computationally intelligent hybrid systems

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