Questions: Simultaneous Localization and Mapping (SLAM)
1 questions to test your understanding
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Question 1 Multiple Choice
In a visual SLAM system, the robot moves forward while a camera observes static landmark features. Over time, odometry (integrating motion estimates) accumulates drift. How does SLAM with loop closure correct this drift?
ALoop closure detects when the robot returns to a familiar location and immediately resets the pose to the past estimate, erasing the accumulated drift
BLoop closure adds a constraint between the current pose and the previously-visited pose that they should be at the same location, then globally optimizes all poses in the trajectory to satisfy all constraints while minimizing total error
CLoop closure marks the drift as an error and re-runs the entire motion estimation from the beginning with updated parameters
DLoop closure is unnecessary; drift naturally vanishes as the robot continues exploring
The complementarity of visual and LiDAR SLAM drives modern sensor fusion approaches: visual SLAM provides rich detail and semantic understanding, LiDAR provides robust metric localization. Multi-sensor SLAM systems leverage both strengths.