STEM与日常科技·英语30篇（7）
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How Self-Driving Vacuum Cleaners Navigate Rooms
扫地机器人如何自主导航房间
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Self-driving vacuums combine LiDAR, cameras, and wheel encoders to map their surroundings.
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They build real-time floor plans by bouncing laser pulses off walls and furniture.
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SLAM software processes sensor data to locate the robot and track its path precisely.
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Obstacle avoidance algorithms help them steer around shoes, cords, and pet toys safely.
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Some models use visual landmarks like door frames to reorient themselves if lost.
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Battery management systems prioritize cleaning high-traffic zones first when power is low.
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Wi-Fi connectivity allows users to schedule cleanings and monitor progress via smartphone apps.
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Advanced versions recognize carpet versus hard floor and adjust suction accordingly.
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Their wheels rotate independently, enabling tight turns and edge-following along baseboards.
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Regular firmware updates improve navigation logic based on aggregated user data worldwide.