Zoran Sjanic

About

Zoran Sjanic is a researcher whose work has advanced the state of the art in autonomous navigation, particularly for unmanned aerial vehicles (UAVs). His primary research focus lies in solving the Simultaneous Localization and Mapping (SLAM) problem—a fundamental challenge for enabling true robot autonomy. Sjanic’s most influential contribution, "A Nonlinear Least-Squares Approach to the SLAM Problem" (2011), with 13 citations, introduced a robust optimization-based framework that improves the accuracy and consistency of state estimation. This work is complemented by his earlier paper, "Solving the SLAM Problem for Unmanned Aerial Vehicles Using Smoothed Estimates" (2010), which specifically addresses the unique constraints of UAVs by fusing camera data with inertial sensors. By moving beyond traditional filtering methods to a nonlinear least-squares formulation, Sjanic has helped pave the way for more reliable autonomous flight and mapping in GPS-denied environments. His research is essential reading for anyone working in aerial robotics, sensor fusion, or real-time perception systems.

Research Focus

Key Achievements

Top Papers

1. 1
   A Nonlinear Least-Squares Approach to the SLAM Problem

   13 citations · 2011
2. 2
   Solving The SLAM Problem for Unmanned Aerial Vehicles Using Smoothed Estimates

   3 citations · 2010

Key Collaborators

Contact & Links