Observer design and state estimation for nonlinear systems. Observer design plays a central role in control applications, since in many cases, some of the system’s states may not be available for measurement. In this subject, I focused on the solvability of the observer design problem for a class of time-varying triangular control systems. For the case of triangular control systems studied in [2], it was shown that under certain weak observability assumptions, the observer design problem is solvable by means of a non-causal time-varying Luenberger-type observer. In [3], we studied triangular control systems that may be unobservable in unknown time-intervals of arbitrary length. It was shown that the observer design problem is solvable by means of a switching sequence of observers with time-delay. Finally, in [C6], we studied that state estimation problem for a class of linear systems with quadratic output measurements. For this particular class of systems, we employed an immersion type technique to extend the system's state by a finite number of components which allows the state estimation to be achieved by means of a linear Kalman-type observer. Finally, by using single range measurements, we studied the position and speed estimation of a vehicle moving in the n-dimensional Euclidean space. The considered class of systems has immediate applications in localization and navigation of autonomous vehicles by using range measurements from a single source. Currently, this methodology has been generalized for general linear and bilinear systems with applications in tracking of systems described by chain of integrators, [U1]. Future work will focus on the problems of navigation and localization of multi-robot system by using single range measurements as well as the distributed state estimation with range measurements from multiple sources.