Emergent Trends in Robotics and Intelligent Systems: Where Is the Role of Intelligent Technologies in the Next Generation of Robots? (Advances in Intelligent Systems and Computing, Volume 316)
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What is the Role of Intelligent Technologies in the Next Generation of Robots ? This monograph gives answers to this question and presents emergent trends of Intelligent Systems and Robotics. After an introductory chapter celebrating 70 year of publishing the McCulloch Pitts model the book consists of the 2 parts „Robotics“ and „Intelligent Systems“. The aim of the book is to contribute to shift conventional robotics in which the robots perform repetitive, pre-programmed tasks to its intelligent form, where robots possess new cognitive skills with ability to learn and adapt to changing environment. A main focus is on Intelligent Systems, which show notable achievements in solving various problems in intelligent robotics. The book presents current trends and future directions bringing together Robotics and Computational Intelligence. The contributions include widespread experimental and theoretical results on intelligent robotics such as e.g. autonomous robotics, new robotic platforms, or talking robots.
is represented by a line expressed in the task space, in a higher dimension the task will be represented by a combination of lines and planes and virtual dynamic variables also being tuned by the tacit learning controller to control the transformation of these geometric entities. 4.2 Motor Control The neural mechanisms used for mapping goals expressed in the task-space into control-space related commands without using internal models remain largely unknown. But many neural systems rely on data
CentroidDefuzzifier(800)); IS.NewRule("Rule 1", "IF Anger IS Medium AND Anticipation IS Medium THEN Aggressiveness IS Low"); … Anger IS High AND Anticipation IS High -> Aggressiveness IS Medium; Joy IS Medium AND Anticipation IS Medium -> Optimism IS Low"; Joy IS High AND Anticipation IS High -> Optimism IS Medium"; Joy IS Medium AND Trust IS Medium -> Love IS Low"; Joy IS High AND Trust IS High -> Love IS Medium"; Trust IS Medium AND Fear IS Medium -> Submission IS Low"; Trust IS High AND Fear
output activity may be expressed as follows: y = s x1 + ... + xn − x1+ n − ... − xm − ϑ (2b) ξ An entity ξ is called the internal potential. Simple implementations of elementary Boolean functions of disjunctions, conjunctions, implication and negation are presented in Fig. 2. 70th Anniversary of Publication: Warren McCulloch & Walter Pitts 3 Let us note that the above mentioned simple principles (1-2) “all or none” for neurons have been introduced in the late twenties and early thirties of
and singing performance of the robot. The algorithm consists of two phases. First in the learning phase, the system acquires two maps in which the relations between the motor control values and the char-acteristics of generated voices are described. One is a motor-pitch map, which associates motor control values with fundamental frequencies. It is acquired by comparing the pitches of generated sounds with the desired pitches included in speaking phrases. The other is a motor-phoneme map, which
• Facilitation of development – when testing algorithms, developers use multiple components. If they want to change a parameter or a part of a system, it is enough to change the parameters of some components. This way they can save time and be more efficient. The above-listed robotic middleware can be used for creating components using various algorithms for artificial intelligence. These components can be used not only in research areas but also in non-robotic fields, for example, home