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This paper presents a comparative study of four control strategies for a flexible joint space manipulator. The considered control strategies consist in the classical Slotine and Lialgorithm, a simple proportional derivative controller, a singular perturbation-based controller and a nonlinear backstepping controller. All control methodologies are assessed in numerical simulations for endpoint positioning while tracking a 12.6 × 12.6 m square trajectory by a two-link flexible joint space robot, thus providing a common framework to compare the respective performance of the considered control schemes. Simulation results indicate that controlling both nonlinearities and joint flexibility effects improve the closed-loop behavior of the space robot where the control of nonlinearities is of greater importance in the sense that it provides the most significant improvements. While each control scheme tracks the trajectory with a different degree of accuracy, the best performance for this particular application is obtained with the nonlinear backstepping control strategy.

This paper presents the 3-D guidance and navigation of mobile/flying robot. A 3-D local trajectory planner has been developed using fuzzy logic. The guidance and navigation has been done in the presence of static and dynamic obstacles.

Data/sensor fusion became an important technique to integrate large amounts of information. Very often, information in form of measurements comes from several different sources, e. g. sensors in forms of measurements. These measurements need to be integrated to form one global information. The global information can be used in decision or control systems. Also, fusion systems are needed to synchronize signals obtained in different time phase. In ideal case, the fused signal is more accurate than any of original signals considered separately.