Expert systems and neural networks are new tools for the control of fermentation processes. With expert systems the fermentation plant and the process itself is modelled via a generalized, qualitative system descripti...
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Expert systems and neural networks are new tools for the control of fermentation processes. With expert systems the fermentation plant and the process itself is modelled via a generalized, qualitative system description based on the experience of human experts. On the other hand neural networks and interpolating associative memories can learn the process behaviour directly by process observation. The paper at hand reports, how both control techniques can be combined for purposes like process supervision, modelling and optimization of biological plants.
Computational complexity of two path planning approaches for a two-dimensional (2D) work space is considered: The approach using safe triangles and the approach based on quadtree. The average cost of establishing work...
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Computational complexity of two path planning approaches for a two-dimensional (2D) work space is considered: The approach using safe triangles and the approach based on quadtree. The average cost of establishing work space representation, i.e. of building the safe triangles and the quadtree respectively, are estimated. Both approaches are simulated to plan paths for numerous work spaces with obstacles which are generated at random. The results of the simulation are summarized to show the expected behavior of each approach. Comparison based on analyses and simulation is presented.
A three fingered, multijointed robot gripper for experimental use is presented. The mechanics as well as the control architecture are designed for this special purpose. The gripper system provides the basic means in t...
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A three fingered, multijointed robot gripper for experimental use is presented. The mechanics as well as the control architecture is designed for this special purpose. The gripper system provides the basic means in te...
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A three fingered, multijointed robot gripper for experimental use is presented. The mechanics as well as the control architecture is designed for this special purpose. The gripper system provides the basic means in terms of position and force control to perform experiments about grasping and object motion in a useful way. The gripper can be used to develop and evaluate different approaches of stable grasping and object manipulation. Results of the control of the gripper on joint level, the Cartesian behaviour of the fingers and some experiences with the grasping and manipulation experiments using the presented system are reported.< >
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