Robust mobile robot navigation is an open problem.
Recent research in mobile robot navigation is focused on integrating the metric and topological paradigms to unsupervisedly construct representations of indoor environments.
Mobile robot navigation is driven by two simultaneous camera images from the environment over which feature points are extracted and matched between successive frames.
Especially in dynamic environments a key feature concerning the robustness of mobile robot navigation is the capability of global self-localization.
A common challenge for mobile navigation design is trying to expose the breadth of content whilst preserving a clean design.
The mere thought of Google 's continued expansion into the mobile navigation market is enough to make any mobile navigation provider nervous.
While using a "hamburger menu" is good for mobile, the rest of the top navigation isn't user-friendly and is definitely lacking some icons that the user may be looking for.
The early mobile navigation environment was chaotic and cutthroat, a dog-eat-dog world of competing operating systems, he adds.
Mobile navigation should be easy-to-use for mobile users and simplified, much like that of Wayfair.com.
