Unmanned Ground Vehicles (UGVs) are currently tele-operated, requiring continuous human assistance. Video streaming between the UGV and the Operator Control Unit (OCU) is challenging under degraded communications, and low-texture indoor environments. Controlling a UGV needs detection and tracking of viewpoint-invariant landmarks, a navigation system for semi-autonomous operation, and a simple user interface for operator command. In a low-texture indoor environment, landmark-based navigation is difficult due to lack of distinctive micro-features such as Shape Invariant Feature Transform (SIFT) and Speeded Up Robust Feature (SURF), which are commonly used image features in computer vision. To address these issues, IAI and its collaborator, University of Pennsylvania have been awarded a contract entitled “Bio-Inspired Visual Navigation: From Landmarks via Bearing to Controls.” The Bio-Inspired Visual Navigation System requires only a standard EO camera payload. A segmentation-based method extracts landmarks as closed contours around visually salient objects in the image, which can be detected even in the low-texture environment. View-invariant shape and topological features are used to recognize these landmarks from different viewpoints. The locations of these landmarks are transformed into visual guides for bearing-only navigation. Finally, an intuitive OCU user interface enables the operator to specify waypoints and destination on an image. Using this interface, the UGV can semi-autonomously navigate its surroundings to the required destination with minimal input from the operator even in a degraded communication environment. A robust and efficient fixation-based landmark tracking algorithm extracts the object boundary, and tracks landmarks smoothly and efficiently even with changes in scale and viewpoints during camera motion. This technology is useful in military surveillance and reconnaissance applications, in civilian search and rescue operations, and to control robots via the Internet or cell phone.