Release notes

Feb 24, 2026Stable 146

Improved Cleaning Time Estimates

Cleaning time estimates are now better tuned to Matic’s current performance, providing more accurate ETAs and improving how the robot plans charging and refill breaks.

Better Support for Large Homes

Added additional infrastructure to support larger maps and more complex home layouts.

More Reliable Edge & Transition Cleaning

Fixed an issue where Matic could skip edge, toekick, or transition cleaning if the floor type changed during an active session (for example, if a rug was added after cleaning started).

Feb 17, 2026Stable 145

Smoother transitions between floor types

Matic now detects changes between carpet and hard floors faster, even in low-light conditions. You'll notice less hesitation when rugs are moved or removed.

Better stuck recovery

We've improved how Matic works to free itself when it gets stuck, so it can get back to cleaning on its own more often.

Improved Resume After Alerts

Fixed an issue where Matic could miss portions of cleaning after resuming from alerts like Sweeper Jam, No Water, or Bag Full. Cleaning now resumes more reliably and completes as expected.

Feb 8, 2026Stable 144

Improved toekick cleaning

Matic now uses motor current sensing to better detect and navigate into toekick spaces beneath cabinets and kickboards, meaning deeper cleaning coverage in those hard-to-reach areas.

One-touch cleaning from dock

Start a full home clean by simply pressing the Play/Pause button while Matic is docked.

Tap to dock

When Matic is off the dock and has no active errors, tap the Play/Pause button to send it back to the dock.

Coverage display fix

Resolved an issue where coverage from a previous session could incorrectly appear during a new cleaning.

Feb 3, 2026Stable 143

Faster Start for Mopping

Matic now skips redundant checks when starting a mopping session if the bag hasn’t been removed since the last check. This reduces startup time and gets cleaning underway faster.

Enhanced Object Detection

Our new neural network model delivers smarter navigation with improved detection of: floating objects (like chair and table legs), low-profile obstacles, dining tables and furniture, stairs and drop-offs.