the robot keeps getting stuck under my kitchen chairs or sofa, says 'trapped' in the app

Diagnosis

The Roborock Q Revo MaxV utilizes a combination of LiDAR (Light Detection and Ranging) and ReactiveAI 2.0 obstacle recognition. The "trapped" error occurs when the robot's LiDAR sensor perceives a gap—such as the space between the floor and the underside of a sofa or the legs of a kitchen chair—as wide enough to enter, but the physical chassis or the top-mounted LiDAR turret becomes wedged. Because the LiDAR turret protrudes slightly, the robot may calculate a clearance of 10cm, but if the furniture dips or the carpet piles up, the chassis creates friction that triggers the bumper sensors repeatedly. This is often exacerbated by "phantom gaps" where the LiDAR sees a clear path, but the robot's physical width (approximately 35cm) is slightly larger than the actual clearance between chair legs. When the robot enters these tight spaces, it can become high-centered or wedged, causing the drive wheels to spin without moving the chassis. The internal IMU (Inertial Measurement Unit) detects that the wheels are turning but the position isn't changing, triggering the "Trapped" alert in the app and forcing an emergency stop.

How to Fix It

To resolve this, you must combine physical boundary settings with software sensitivity adjustments to prevent the robot from attempting to enter "tight-fit" zones.

1. Open the Roborock app and navigate to the "Map Management" section from the main cleaning screen.
2. Select "Edit Map" and then choose "No-Go Zone."
3. Draw a rectangular boundary around the kitchen chair area and the underside of the sofa. Do not draw the box exactly to the edge of the furniture; instead, extend the boundary by 15cm to 20cm beyond the furniture legs to ensure the robot doesn't try to "peek" under the edge.
4. Navigate to "Settings" (the three dots in the top right) and go to "Robot Settings" > "Detection Settings."
5. Locate the "Collision Sensitivity" toggle. Switch this from "Medium" to "High." This forces the bumper to trigger a "turn-around" command at the slightest contact, preventing the robot from pushing itself deeper into a tight wedge.
6. If you have the "Obstacle Avoidance" setting, ensure it is set to "Standard" or "High" rather than "Low," as this enables the ReactiveAI cameras to better identify the narrow gaps that LiDAR might miscalculate.
7. Save the map and run a "Full Home" clean to verify the robot now bypasses these zones entirely.

If That Didn't Work

• Physical Furniture Risers: If the robot is getting stuck under a sofa that is just millimeters too low, install 1-inch rubber furniture risers. Increasing the clearance from 4 inches to 5 inches removes the physical friction point entirely, allowing the robot to clean under the sofa without triggering the bumper.
• Virtual Wall Deployment: If the software No-Go zones are being ignored (which can happen during "Deep Cleaning" modes), use a physical magnetic strip or a physical barrier. While the Q Revo MaxV relies heavily on LiDAR, placing a subtle physical block or a piece of furniture (like a decorative plant) at the entrance of the "trap zone" forces a physical detour.
• Reset the LiDAR Turret: Check the top-mounted LiDAR turret for any debris or hair wrapped around the rotating head. If the turret is slightly tilted or obstructed, the distance readings will be off by a few centimeters, causing the robot to think it can fit where it cannot. Use a can of compressed air to clear the sensor.
• Modify Carpet Settings: If the robot is getting stuck specifically on carpets under chairs, change the "Carpet Cleaning" setting to "Avoid" or "Mop Only" for those specific zones. The increased friction of the carpet can pull the robot's chassis lower, making it more likely to wedge under low-hanging furniture.

Heads Up

• Avoid placing dark, non-reflective rugs under your kitchen chairs; the infrared sensors can sometimes misinterpret deep black fabrics as "cliffs," causing the robot to behave erratically or pivot sharply into a chair leg.
• Regularly clean the ReactiveAI camera lenses on the front of the unit with a dry microfiber cloth. Smudges on the lenses reduce the robot's ability to recognize the "legs" of chairs, relying instead on the less-precise LiDAR.
• Check the side brushes for wear. If the side brushes are frayed or bent, they can catch on the edges of furniture legs, pulling the robot into a skewed angle that makes it more likely to get wedged.
• Ensure the robot's firmware is updated to the latest version. Roborock frequently releases "Navigation Logic" updates that specifically improve how the robot handles tight corridors and furniture gaps.