Obstacle Avoidance (Robot)

The active binocular camera and structured-light system give the S1 Pro excellent obstacle avoidance, with lab tests and real homes showing it reliably recognizing and steering around common clutter while still letting sensitivity be tuned for pet hair and other tricky debris.

AIVI 3D obstacle avoidance does an excellent job steering around common household items such as cables, reducing the risk of tangles and stuck situations.

Excellent obstacle avoidance around cords, toys, and pet messes, reducing interventions during daily runs.

Laser and camera based sensing avoids hazards reliably, stopping at stair edges and steering around small objects like cords, shoes, and bins, and users report it successfully detecting unexpected loose cords and clutter while still completing cleaning runs.

Obstacle avoidance is a highlight, with cameras and sensors dodging most household hazards and scoring near perfect in structured tests.

Reviews consistently highlight the Z70’s outstanding obstacle avoidance, with its 3D Time of Flight camera system scoring far above average in tests and reliably steering around everyday clutter.

Obstacle avoidance is a standout strength of the X50 Ultra, with its sensors correctly identifying and routing around shoes, cords, and fake pet waste while labeling hazards in the app and maintaining safe distances during cleaning.

Recent testing highlights the Freo Z Ultra as one of the best robots for obstacle avoidance, reliably recognizing cords, shoes, and even fake pet poop so it can steer well clear of problem areas while still navigating everyday clutter and pet messes.

Reviews now highlight near-perfect obstacle avoidance, with the Qrevo Master accurately recognizing and steering around furniture and small items and even passing formal small obstacle tests with a 100% success rate.

The X10 Pro Omni’s AI.See obstacle avoidance uses a front camera, lasers, and a spotlight to recognize over a hundred object types and ranks near the top of obstacle tests, though its cautious behavior can sometimes make it treat piles of debris as obstacles.

Obstacle avoidance is consistently top-tier, combining LiDAR navigation with a camera and structured-light sensing to recognize and avoid many common household objects. Some reviewers note it can photograph obstacles and is especially reliable at finishing cleans without intervention, though loose cables can still be challenging for any robot.

Cliff sensors avoid stairs/ledges; basic bumper navigation around furniture.

PrecisionVision camera-based avoidance is a category strength, steering around cords, toys, and pet waste and enabling Keep Out zones plus obstacle photos for feedback; performance depends on lighting and isn't perfect on first runs in clutter.

The P50 Pro Ultra’s camera-plus-3D structured light obstacle avoidance remains solid for the price, often rivaling more expensive robots at spotting and steering around clutter even though it can still occasionally snag or ride over flat floor cables.

The P10 Pro Ultra’s camera-based obstacle avoidance scores above average, recognizing many object types and outperforming other robots in its price bracket at avoiding clutter.

Its obstacle avoidance system scores well above average in testing, helping the X9 steer around common household hazards more confidently than typical robot vacuums.

Obstacle avoidance performance slightly exceeds the Yeedi S14, placing the Saros 10 near the top of tested robots for reliably steering around common hazards.

AI obstacle avoidance can recognize common household clutter and pet accidents, an area where Roombas are expected to remain among the stronger performers compared with many rivals.

Camera based system recognizes and avoids household objects and supports keep out zones, helping prevent stuck events.

Camera-based system recognizes and avoids common household objects and is backed by iRobot’s pet waste avoidance guarantee.

3DAdapt sensors steer around common hazards while Pathfinder planning keeps routes efficient in typical home layouts.

3DAdapt sensors help the CE avoid everyday hazards while Pathfinder planning maintains efficient room coverage.

Obstacle avoidance is strong for common items like shoes and cables and works in low light; however, it may still interact with small clutter and lacks camera-based pet waste detection/remote viewing found on some flagships.

Obstacle avoidance is generally strong with AI.See/AIC vision plus LiDAR, often steering around cords, socks, and toys, but it can be overly cautious or still snag thin cords/curtains on occasion, so no-go zones and tidying help.

Reactive obstacle avoidance reliably steers around common items like cords and flags obstacles on the map, performing comparably to camera equipped models in most homes.

Strong camera assisted obstacle avoidance that reliably flags and steers around pet waste and other objects, ranking among the best tested though still only average with low lying cables.

Multiple tests show the L40’s camera and sensor system is significantly above average at recognizing and avoiding household objects, ranking near the top of obstacle-avoidance charts even if the X40 is slightly better.

The Combo 10 Max uses an RGB camera and light to deliver above-average obstacle avoidance, successfully dodging most common floor hazards though it still makes occasional mistakes.

The AV2800ZE’s NeverStuck system and 3D sensing let it climb small obstacles and avoid getting stuck, while lifting the mop to keep carpets safer during tricky crossings, though it can still struggle with low-lying clutter and some doorway thresholds.

Obstacle avoidance is good but not flawless: the S8 MaxV Ultra reliably goes around larger objects like boxes and candles but still bumps small items such as remotes often enough to land in the upper-middle of avoidance rankings.

Obstacle avoidance is a clear strength, as the S8 Pro Ultra reliably works around larger items like boxes and candles and earns near-top scores even though it may still bump smaller objects occasionally.

Camera-based obstacle avoidance is a bit more reliable than the S5X, usually steering around clutter and spotting pet accidents while only occasionally clipping or missing low cords and getting lightly stuck.

Its obstacle-avoidance system typically does a good job steering around toys, furniture, and pet messes without frequent tangles, though it may slow or pause when it meets unexpected objects that are not yet on the map.

Infrared and LiDAR sensors avoid most obstacles with only occasional hiccups; no-go zones add control.

Obstacle avoidance scores are above average with modern camera and structured light sensors, though they still trail the slightly better performing Saros 10.

Even without advanced obstacle detection, the V3s Pro generally steers around common household objects and rarely gets badly stuck.

The P10 Ultra’s updated obstacle avoidance is billed as a step up from previous 3i models, helping it recognize and steer around common clutter while it works its way along walls and edges.

Front-facing IR sensors generally help it slow and steer around legs, toys, and people, though it can still bump or push lighter objects and sometimes fails to notice low cords lying flat on the floor.

Roborock’s obstacle avoidance on the Saros 10R is mixed, reliably steering around larger hazards like fake pet waste but still running over cords and shoe laces often enough that owners may need to tidy up cables to prevent occasional jams.

Sensor-based obstacle avoidance generally steers the S5X around toys and furniture and flags obstacles in the app, though loose power cords and low cables can still trip it up.

Onboard vision and AIVI 3D 3.0 help the robot avoid cables, table legs, toys and even give pets a wide berth better than older Yeedi models, though light rug fringes and occasional dark-room cable tangles and slightly less precise object avoidance than some rivals keep it short of the very best performers.

Obstacle avoidance on the N30 Omni is generally good for everyday clutter, but without a front camera it is more likely than flagship robots to snag on cords and shoelaces unless floors are tidied first.

Reactive AI obstacle avoidance on the Edge S5A generally steers around larger toys and clutter but still tends to run over low cables, giving it decent but imperfect avoidance.

Obstacle avoidance on the Deebot X8 Pro Omni is generally strong, with its AV 3D camera and lidar system usually steering smoothly around furniture, pets, and common floor clutter in normal lighting, but tests and user feedback show it can still run over small cords, toys, or rug tassels more often than the very best robots.

Obstacle avoidance is serviceable, using a camera and structured light to reach roughly average performance in testing.

Obstacle handling is mixed: it recognizes furniture, mats, and other objects reasonably well, but loose items like mats or shoes can still cause minor tangles or missteps.

Obstacle avoidance works only part of the time, performing below top-tier models though acceptable for the price range.

Obstacle avoidance performance is roughly average based on standardized object tests.

Obstacle avoidance is limited (typically basic IR and LiDAR without camera-based object recognition). Reviews mention it can avoid larger items like shoes but often struggles with low cables, socks, toys, and simulated pet messes, making floor prep and no-go zones important.

Obstacle avoidance is average: the Q Revo Pro can successfully route around larger objects like boxes and candles but still hits smaller items such as remotes often enough to keep it out of the top ranks.