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The ability to reliably detect vegetation is an important requirement for outdoor navigation with mobile robots as it enables the robot to navigate more efficiently and safely.
Titan is a mobile robot built for outdoor navigation research.
However, for outdoor navigation methods, dynamic changes in the environment still remains as a major problem.
Outdoor navigation methods using LIDARs or cameras have been proposed (e.g. [10],[10]).
We have proposed an outdoor navigation method called "MN (Magnetic Navigation) [3],[4]".
It is, therefore, necessary to strengthen the robustness of the outdoor navigation methods against changes in the surroundings.
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We achieved outdoor autonomous navigation over 2 km by using the MNPC [6].
This technique has been utilized mostly in robotics [6], but there are some other adaptations of it for indoor and outdoor pedestrian navigation as well [7 10].
Whereas positioning and navigation outdoor have become ubiquitous and affordable over the last decade or so, providing similar services in indoor environments is extremely challenging.
JPL's Darmindra Arumugam and his team created a system, called Precision Outdoor and Indoor Navigation and Tracking for Emergency Responders (POINTER), that relies instead on what are called quasistatic fields.
Thus, passive stereo cameras keep on being employed for outdoor applications related to navigation [25] whereas active ones are leading the indoor application usage.
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