STEM与日常科技·英语30篇（7）

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扫地机器人如何自主导航房间

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