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GausiumCombo / multi-function
Gausium Mira
Mid-size sweep-and-scrub in one pass, no pre-mapping ('Drop & Go'). Onboard tank self-cleaning.
SweepMopScrub
Coverage
2,016 m²/h (theoretical max)
Clean width
400 mm
Runtime
4 h
Weight
130 kg
Why it stands out
- Sweep + scrub single pass
- No pre-mapping deployment
- Onboard self-cleaning tanks
Full specifications
| Coverage (published) | 2,016 m²/h (theoretical max) |
| Cleaning functions | Sweep, Mop, Scrub |
| Floor types | hard |
| Clean width | 400 mm |
| Clean / recovery tank | 22 / 20 L |
| Dust bin | n/a |
| Battery | 60 Ah |
| Runtime per charge | 4 h |
| Charging time | — |
| Max speed | 1.4 m/s |
| Navigation | 3D perception + LiDAR ('Drop & Go') |
| Obstacle avoidance | 3D perception, LiDAR, ultrasonic |
| Gradeability | 6° |
| Threshold crossing | Not published |
| Min aisle width | 66 cm |
| Noise | Not published |
| IP rating | Not published |
| Weight | 130 kg |
| Dimensions (L×W×H) | 680 × 550 × 900 mm |
| Auto water dock | No |
| Elevator / multi-floor | No |
Manufacturer-published specs (source: gausium.com/specs/mira). “Not published” = the maker doesn't disclose it; we don't estimate those.
How many would your site need?
Measure your floor area from a plan, then size a fleet and see the labour it saves. ROI & payback included.
Pricing:est. A$ 49,246 ex-GST · roboticfloorcleaner US$29,999 +20% → AUD ×0.9
Where we've sized the Gausium Mira
Worked examples with fleet counts, labour displaced and payback.
- Industry InsightsPUDU vs Gausium vs CenoBots: 17 Machines, One Rule, Three Different WinnersWe put every comparably-priced machine in our catalogue on one derated throughput basis and one AUD footing. No brand wins every class — and the assumptions that decide the close calls aren't printed on any spec sheet.
- Case StudyOne Robot Model Across Six Hotels: 9 Units, 100% Daily Floor, 24-Month PaybackA composite case study: a six-property hotel group standardising on one autonomous scrubber so the floor looks the same at 3pm everywhere. Why the cheapest machine and the fastest machine both lost, and the group-wide payback math.
- Case StudyThe Leisure Centre That Cut Hard-Floor Cleaning Hours 58% — On a Floor That Never Sits StillA composite case study: choosing a sweep-and-scrub robot for a busy aquatic & leisure centre where the studios reconfigure daily and the change rooms never stop. Why the higher-throughput robot won a five-hour window with no forgiveness, and the payback math behind it.
- Case StudyA 9,000 m² Hospital Night-Clean: Three Scrubbers, One OperatorA composite case study: sizing an autonomous scrubber fleet for a hospital's quiet hours on a uniform spec-derated basis — and an ~11-month payback.