Robotic Floor Mopping Gets Smarter: What’s New for Pudu CC1 & CC1 Pro (Autonomous Floor Scrubber Updates)

Robotic floor mopping looks “hands‑off” in a demo — but in real buildings it’s all about repeatability: catching stubborn stains, hitting the places that get dirty fastest, and giving supervisors proof of what happened.

Pudu’s CC1 and CC1 Pro (an autonomous floor scrubber / robotic floor scrubber platform) continue to improve through software, and this release focuses on closing the loop between what the robot cleaned, what it couldn’t fully clean, and how your team follows up.

If you manage cleaning across retail, malls, transit, or high‑traffic facilities, the headline is simple: more targeted cleaning, less rework, and better visibility.

For reference, you can explore the robots here:

What’s new for CC1 / CC1 Pro (high impact)

Co‑Botics: Guided Cleaning Mode (human‑robot collaboration)

Guided Cleaning Mode introduces a practical workflow for stubborn stains. During routine cleaning, the robot evaluates cleaning results using its cleaning-effect detection and creates a heat‑map style record of stubborn stain locations. In guided mode, the robot then leads an operator to each location for manual handling and confirmation.

This creates a closed loop:

Automatic cleaning
Assisted confirmation (robot guides to remaining problem spots)
Manual re-cleaning (targeted, verified)

Best for: malls, supermarkets, subway stations, and other environments with frequent gum/adhesive residue or tracked-in grime.

Operational note: guided mode depends on cleaning-effect detection being enabled, and the robot must have completed at least one automatic cleaning run that day on the same localization map.

Ultra Spot Cleaning (rapid “high value” cleaning passes)

Ultra Spot Cleaning lets CC1 Pro use historical trash/dirt heat map data to quickly clean areas that get dirty most often — great when you have a short window (before opening, between rushes, after a spill-heavy period).

If a task has no prior history, the robot will fall back to a quick inspection + routine clean to build the baseline.

Summon Cleaning V1.0 (CC1 + MT1 collaborative cleaning)

If your site runs both CC1 series (wet stains / floor scrubbing) and MT1 series (large solid debris), this is a big efficiency unlock.

When a robot detects something it cannot handle, it can record the location and summon the other robot to complete the job after the task finishes.

CC1 Pro can summon when its AI recognizes large solid waste it can’t handle
MT1 can summon when it recognizes wet stains/oil it should avoid

This is effectively “call-to-clean” coordination — more precise than relying on manual discovery later.

AI improvements (less false positives, better long-term accuracy)

AI manual exemption + automatic exemption

AI‑enabled robots (like CC1 Pro) can now mark areas that are commonly misidentified as dirt/obstacles (floor patterns, cracks, terrazzo, unusual tiles).

You get two options:

Automatic exemption: the robot learns repeated false positives and stops flagging that location (dirt types)
Manual exemption: an operator reviews the robot’s camera view and taps the recognition boxes to exempt specific spots

This reduces unnecessary slowdowns/avoidance behavior and helps keep coverage consistent.

AI recognition model online OTA

In SC5.19.41, AI recognition models can be upgraded via OTA independently from the full software version. This matters in the real world because floors, lighting, and “weird obstacles” vary site to site — and improving recognition used to require heavier update workflows.

If you’re operating CC1 Pro in a facility with unusual floor colors, patterns, or recurring objects, this capability can reduce time-to-fix for recognition tuning over time.

Ops-focused updates that reduce friction

Hibernation Period (scheduled shutdown windows)

You can now configure a Hibernation Period by date so scheduled tasks won’t auto-start during closures (holidays, renovations, temporary shutdowns). This is especially useful for sites with after-hours alarms.

Automatic map noise removal (cleaner maps, fewer path failures)

Mapping now includes automatic noise removal at the end of map creation. In practice, this can reduce the small “ghost pixels” that sometimes cause:

Bow-shaped cleaning paths to deform
Manually taught paths to fail

In most sites, this reduces the need for manual map cleanup after mapping.

Cleaning reports now include cancellation/interruption reasons

If a task gets canceled or interrupted, cleaning reports can now show the reason (e.g., manual cancel, low power, water shortage, wastewater full). This makes troubleshooting faster without digging through logs.

Experience optimizations (the “it just works better” list)

This release also includes a set of practical optimizations that help day-to-day reliability:

AI Adaptive Cleaning V2.0: more accurate dirt localization and speed control to reduce efficiency loss during adaptive adjustments
Automatic Restart V1.0: auto-restart and resume cleaning after serious system-level errors
Self-cleaning roller brush compartment improvements: compatible with optional self-cleaning water tank
Clean water tank flow control optimization: better utilization of remaining clean water to extend run time
Loop cleaning path optimization: improved planning for irregular areas to complete loops more efficiently
Remote desktop manual reposition button: quicker recovery when you need to reposition the robot remotely
Better prompts/confirmation: clearer behavior when canceling during water/power replenishment
Teach path verification: verifies obstacles near start/end points to reduce teach-path failures
Expanded mapping hints: improved text + image guidance for better map expansion results
Low power mode optimization: low-power mode works while charging, reducing standby fan noise
Additional languages: Turkish, Vietnamese, and Finnish

Bug fixes (notable)

Elevator ride optimization: reduces issues related to map switching when riding elevators on large maps
Scheduled task edge case fix: resolves a low-probability case where scheduled tasks starting on the hour could fail

Practical “next steps” after updating

If you’re rolling this out to CC1 / CC1 Pro in production, here’s a simple checklist:

Run one standard automatic cleaning task (with cleaning-effect detection enabled) so Guided Cleaning Mode has the day’s baseline data.
Create an Ultra Spot Cleaning workflow for high-traffic areas (front entrances, checkouts, restrooms, food courts).
If you run MT1 + CC1 together, review collaborative placement and map pairing so Summon Cleaning can work as intended.
Use AI exemptions in the first week to remove recurring false positives (especially on patterned floors).
Update your closure SOPs to use Hibernation Period instead of disabling schedules manually.

Where this helps most (robotic floor mopping + floor scrubbing use cases)

If you’re evaluating or operating an autonomous floor scrubber (or a robotic floor mopping program) these changes map directly to the biggest operational pain points:

Stubborn stains that “survive” a normal pass: Guided Cleaning Mode makes those misses visible and actionable.
High-traffic zones that get dirty repeatedly: Ultra Spot Cleaning prioritizes the areas with the highest probability of debris/dirt.
Mixed mess types across a facility: Summon Cleaning improves coordination between a floor scrubbing robot (CC1/CC1 Pro) and a debris-focused robot (MT1 series).
Patterned floors causing false detections: AI exemptions reduce slowdowns and unnecessary avoidance behavior.
Stakeholders asking “why didn’t it finish?”: richer task interruption/cancellation reasons reduce troubleshooting time.

CC1 / CC1 Pro resources (internal links)

If you want operator-friendly documentation to support the rollout, these guides are a good starting point:

Want help deploying CC1 / CC1 Pro?

If you want help planning a rollout, updating SOPs, or validating results in your facility: