How do robot vacuums navigate, and are they worth it?

Through one of three navigation approaches, and the difference between them determines almost everything about how well the machine works.

Random or bump navigation. The cheapest approach — the robot moves until it hits something, turns and continues. No map, no memory.

Why it works badly: coverage is statistical rather than systematic, so it takes far longer, misses areas entirely, and repeatedly covers others. It cannot resume where it left off, and cannot be told to clean one room.

Gyroscope and camera-based navigation, which is a middle tier — some sense of position, partial mapping, more systematic movement.

LiDAR (laser) navigation. A spinning laser on top measures distance to surroundings hundreds of times per second, building an accurate map. This is the approach that makes robot vacuums genuinely useful.

What LiDAR enables:

Systematic coverage in efficient parallel rows rather than random wandering.

Persistent maps across sessions, with room labels.

Room and zone selection — cleaning one room on request.

No-go zones, defined in software rather than with physical barriers.

Resume after charging, returning to where it stopped.

Working in the dark, unlike camera navigation.

Are they worth it? Honestly assessed:

What they do well: maintaining a baseline of cleanliness through frequent light cleaning. A floor vacuumed daily never gets very dirty, and this is genuinely valuable — particularly with pets or in households where nobody has time.

What they do badly: deep cleaning, edges and corners despite side brushes, thick carpet, stairs, and anything requiring judgement. Suction is generally well below a decent upright.

The preparation problem. They need floors clear of cables, socks, small toys and anything a brush can eat. Households that cannot maintain that find them frustrating.

Maintenance is real — emptying, brush hair removal, filter cleaning, sensor wiping.

They supplement rather than replace a proper vacuum.

Camera-equipped models raise privacy questions worth considering.