A heuristic approach for path planning for redundant robots

A new method to solve the trajectory generation for a redundant manipulator is proposed. It avoids traditional computationally intensive methods by relying on the human experience; The proposed method uses a fuzzy logic controller to generate the magnitude of the angles needed to move the end effector to the next target point. The inputs to the controller are the desired displacement of the end effector and the elements of the jacobian matrix that correspond to the considered joint, while the output is the angle magnitude of the joint needed to reach the target point; An algorithm is used to determine the sign of the output from the fuzzy logic controller. Inverse kinematics is used to bring the end-effector to the target point; Several fuzzy logic controllers combined with heuristic algorithms are used to avoid the obstacles in the workspace and to avoid self collision of the links

Investigation on soft computing techniques for airport environment evaluation systems

Spatial and temporal information exist widely in engineering fields, especially in airport environmental management systems. Airport environment is influenced by many different factors and uncertainty is a significant part of the system. Decision support considering this kind of spatial and temporal information and uncertainty is crucial for airport environment related engineering planning and operation. Geographical information systems and computer aided design are two powerful tools in supporting spatial and temporal information systems. However, the present geographical information systems and computer aided design software are still too general in considering the special features in airport environment, especially for uncertainty. In this thesis, a series of parameters and methods for neural network-based knowledge discovery and training improvement are put forward, such as the relative strength of effect, dynamic state space search strategy and compound architecture. [Continues.