Grant: Discovery Grants Program - Individual

Over the years research in robot manipulators has been increasing rapidly. This has led to the development of efficient conventional methodologies for simple industrial robot manipulators capable of performing simple tasks. However, there is already a great need in the Service, Industry, and Space, sectors for complex robotic systems (such as manipulators with many degrees of freedom, multi-manipulator systems, and/or robotic systems being re-configurable) that can perform complicated tasks. Furthermore, many of the developed conventional approaches turn out not to be entirely generic and their efficiency for complex robotic systems is not considered conclusive for on-line and truly real-time operations. Consequently, it is necessary to devote research efforts to the development of novel methodologies for complex robotic systems. In order to ensure effective real-time implementations and successful results for complex robotic systems it is necessary to develop and implement under a common Framework some Artificial & Computational Intelligence, and/or Soft Computing, (Artificial Neural Networks, Fuzzy Inference Systems) techniques. The proposed research program is focused on developing, under a common Framework, Artificial Neural Networks and Adaptive Fuzzy Inference Systems methodologies for their implementation on a key robotics and industrial technology area: The Intelligent Motion Planning of Robot Manipulator Systems. The proposed research will successfully accomplish: the realization of computationally fast algorithms for the truly real-time operation and motion planning of complex Robot Manipulator Systems. Furthermore, it will also provide new insights for the development and implementation of advanced robotics systems to be used in the near future in the Service, Industry, and Space sectors.