When GPS is unreliable, jammed, spoofed, blocked by concrete, or unavailable underground, autonomous systems still need to know where they are and where they are going. This is where SLAM-based navigation becomes essential. SLAM, or Simultaneous Localization and Mapping, allows a vehicle, robot, drone, or wearable system to build a map of its surroundings while estimating its own position inside that map. In GPS-denied or contested areas, the best navigation systems are not usually dependent on one sensor or one algorithm; they combine perception, inertial sensing, robust mapping, and real-time decision-making into a resilient autonomy stack.
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