AI has become a defining theme across commercial cleaning robotics—but genuine intelligence remains rare.
In large, dynamic environments, many robots still struggle to deliver consistent results. Edges are missed, performance fluctuates under changing lighting or traffic conditions, and outcomes often depend on manual follow-up. The issue is not a lack of features, but a lack of real environmental understanding.
With the launch of the PUDU BG1 Series, Pudu Robotics introduces a new paradigm: AI-native cleaning. Rather than layering AI onto existing machines, this approach redefines how a robot perceives its surroundings, makes decisions, and executes tasks. It represents a shift from automation toward systems that can continuously adapt to real-world conditions. Together with the PUDU CC1 Series and PUDU MT1 Series, the BG1 series completes Pudu’s AI-native cleaning portfolio—covering diverse scenarios and establishing a scalable foundation for intelligent floor care.
This shift also redefines how performance is measured. The key question is no longer how large or powerful a machine is, but how effectively it can understand, decide, and act.
01 The AI-Native Paradigm: Beyond "Hardware-Centric" Thinking
For years, progress in cleaning robotics has been driven primarily by hardware—larger tanks, longer runtime, and more complex mechanical structures. AI, when introduced, typically played a supporting role, improving navigation or recognition. This model is reaching its limits. As environments become more dynamic, systems built on predefined logic struggle to adapt.
Pudu Robotics reframes this approach by redefining the relationship between hardware and intelligence:
AI-Native Cleaning Robot = Precise executed "Hardware Degrees of Freedom" × Ever-evolving "AI Degrees of Freedom"
"Hardware Degrees of Freedom" refers to the robot’s ability to act in the physical world. Instead of fixed mechanisms, it becomes a flexible execution system. In the BG1 Series, sweeping and scrubbing are coordinated rather than sequential. Brushes can adjust pressure and height independently, and extendable structures allow the robot to clean directly along edges. This expands the robot’s “action space,” enabling more precise and adaptable execution.
"AI Degrees of Freedom" defines the system's ability to interpret and respond to its environment. Beyond recognizing objects or dirt, the robot understands context—such as movement patterns, lighting conditions, and spatial changes—and adjusts its strategy in real time.
What defines an AI-native system is the integration of these two dimensions. Hardware is no longer passive, and AI is no longer an add-on. They are designed as a unified system from the outset.
Their relationship is multiplicative: without execution flexibility, intelligence cannot be applied; without intelligence, hardware becomes repetitive.
Only when both evolve together can a robot transition from a task executor to an intelligent agent capable of understanding and optimizing its work.
At this point, cleaning robots achieve a complete operational loop: Perception → Decision → Execution → Feedback → Learning.
This closed loop is the foundation of AI-native cleaning.
02 AI Magic Cleaning: Constructing the Skill Closed-Loop
If AI-native defines what the system is, AI Magic Cleaning defines how it works in practice.
Rather than following fixed workflows, cleaning becomes a dynamic, adaptive process. The system continuously interprets the environment, selects the appropriate action, evaluates the result, and adjusts as needed.
The shift begins with perception. The robot does not simply navigate space—it interprets it. Stains are identified and classified, while dynamic factors such as movement and environmental variation are incorporated into decision-making.
Based on this input, the system determines how to act. Rather than relying on predefined rules, it selects the appropriate cleaning strategy in real time. It can prioritize different types of debris, adjust cleaning intensity, or decide whether additional passes are necessary. These decisions are made rapidly, allowing the system to respond as conditions change.
Execution is tightly linked to this decision layer. The flexibility of the hardware ensures that each strategy can be carried out precisely, translating intelligence into effective cleaning performance.
The system also evaluates outcomes. If results fall short of expectations, it adjusts and continues; if objectives are met, it proceeds to the next task. This feedback mechanism ensures that cleaning is verified rather than assumed.
Over time, accumulated data allows the system to refine its responses. Patterns across environments inform future decisions, enabling continuous improvement without manual reconfiguration.
03 From Tool to AI-Native: The Evolution of Pudu’s Cleaning Portfolio
The BG1 Series is not an isolated breakthrough but the result of a clear technological trajectory.
Phase 1: Automation — Mechanizing Repetitive Labor
The first stage was dominated by traditional cleaning robots and semi-automated equipment. These machines were mostly mechanical upgrades to floor scrubbers and push-cleaning tools. Add a motor, and the machine can move by itself. Add a basic sensor, and it can avoid obvious obstacles. Use simple timers and route settings, and it can repeat the same task. This stage did free people from the heaviest and most repetitive labor, but the machine itself still did not understand the scene. In environments with frequent shelf changes, dynamic traffic, or complex floor conditions, the limitations became obvious quickly.
Phase 2: Intelligence — From Execution to Perception
The turning point came with PUDU CC1. As one of the first truly intelligent cleaning robots in the industry, CC1 did not stop at being a machine that could move on its own. It integrated sweeping, scrubbing, vacuuming, and dust mopping into a single platform, with one sensing and control system coordinating the workflow. More importantly, CC1 introduced AI capability, allowing the robot to do more than "see" the environment — it could understand part of it. With better mapping and path planning, it improved reach in complex spaces. With smarter obstacle avoidance and edge logic, it improved coverage and efficiency. In this stage, the cleaning robot moved from automation to intelligence.
Phase 3: AI-Native — From Understanding to Autonomous Optimization
The third stage is now being shaped by CC1 Pro, MT1 series, and BG1 series. This is the key step from "a cleaning robot with AI functions" to AI-native cleaning robots. In this stage, AI-native capability is no longer limited to one product. It becomes the shared foundation of Pudu's cleaning portfolio and is expressed differently across product types and scenarios.
PUDU CC1 Pro builds on the all-in-one cleaning platform, significantly enhancing the AI stack. It refines core capabilities such as stain recognition, debris classification, and task orchestration. In medium-sized, multi-functional environments, CC1 Pro demonstrates how a robot can become progressively more effective through continuous use—adapting its strategies based on accumulated experience.
PUDU MT1 Series (including MT1, MT1 Max, and MT1 Vac) focuses on large-scale dry cleaning scenarios. Equipped with AI vision, ultra-wide scanning, and multi-sensor fusion, these robots shift from passive cleaning to active inspection-driven cleaning. They identify debris in real time during operation and immediately respond—enabling a "detect-and-clean" workflow rather than a scheduled, path-based one. This marks a transition from perception to situational awareness.
PUDU BG1 Series extends AI-native capabilities into large-scale cleaning environments, where operational complexity is significantly higher. It combines high-degree mechanical freedom with real-time AI orchestration, enabling coordinated multi-action cleaning strategies across expansive, dynamic spaces. Here, AI is not just guiding movement—it is managing an entire system of interdependent cleaning actions.
Together, these product lines form a cohesive AI-native capability matrix, covering a wide spectrum of cleaning scenarios—from compact, multi-purpose environments to large, industrial-scale operations.
With deployments spanning retail, transportation, industrial facilities, and property management worldwide, Pudu has accumulated millions of hours of operational data. This data continuously feeds back into system optimization—making each new generation more capable and more reliable.
The BG1 Series stands on this foundation, representing the transition from "robots with AI" to AI-native cleaning systems designed from first principles.
04 The Inventor's Spirit: Rewriting the Question
If you only look at features, BG1 can be described as a set of technical innovations: a more complex structure, a smarter system, and a more efficient cleaning method. But once these innovations are viewed together, they reveal a deeper way of thinking — a classic inventor's path.
The essence of that path is not to optimize existing answers. It is to return to the original question and ask whether it was framed correctly in the first place.
Making the boundary disappear: extendable edge cleaning
Large scrubber-dryers have always faced a familiar challenge: edge cleaning. Because key components take up space inside the machine body, the brush often cannot reach close enough to walls and shelving, leaving small areas that still need manual touch-up. BG1 addresses this with an extendable scrubbing brush structure that can move outward when needed, helping the robot clean closer to edges without making the machine smaller. Paired with edge-recognition and collision control, the system balances coverage and safety to deliver cleaner results with less manual follow-up.
From process execution to intelligent routing: rethinking sweep-and-scrub
In conventional cleaning, sweeping and scrubbing are usually treated as two separate steps. That works in manual operations, but in robotics it often means extra travel and lower efficiency. With AI Magic Cleaning, BG1 can decide how to clean based on the scene. Dry debris can be swept first, wet spills can be handled directly by the scrubbing module, and stubborn stains can trigger stronger cleaning settings. Instead of following a fixed sequence, the robot adapts its cleaning strategy to the floor in front of it.
Automatic disc-brush mounting: designing for the people who use it
Maintenance is often overlooked, but it matters just as much as cleaning performance. Replacing a disc brush on traditional equipment usually requires bending down, manual alignment, and tools. BG1 series simplifies this with an automatic disc-brush mounting system. The operator simply places the brush in position, and the robot handles the alignment and locking automatically in seconds. It is a small design change, but one that makes daily operation easier, faster, and more user-friendly.
05 The Power of Long-Term Thinking: Making Innovation a Capability
It is hard to explain BG1's development with a single technology. What really supports the machine is Pudu's long-term accumulation in both technology and real-world deployment.
AI has never been valuable because of a model name alone. Its value lies in whether it can work reliably in the real world. Pudu has invested consistently in cleaning robotics, and every generation has been deployed across different countries and industries. That has created a deep base of real-world operating experience: how dirt behaves on different floor materials, how traffic patterns change throughout the day, and where robots are most likely to struggle in unfamiliar environments. These insights have gradually been absorbed into algorithms and operating strategies.
When BG1 appears as an AI-native platform, it is not a design that was created from scratch in isolation. It is built on years of trial, error, refinement, and accumulated know-how, now systematized into a new platform for large-scale spaces.
At the same time, innovation at Pudu is not treated as a one-time burst. It is a cycle. Lessons from earlier products help improve new algorithms. New products then expand that understanding across broader environments, feeding the next round of iteration. BG1’s AI compute platform and AI Magic Cleaning capabilities have been refined through that same loop. This allows product evolution to follow a clear methodology instead of relying on accidental inspiration.
Pudu’s long-term thinking is also reflected in its customer-first approach. When deciding whether to invest in a feature, the product team does not start from novelty. It starts from a basic question: does this solve a real pain point, and does it create durable value in day-to-day operations?
That is why many of the most important BG1 details are not flashy at first glance. A simplified maintenance process. Easier onboarding for operators. Stable long-term uptime. These are not afterthoughts. They are design principles.
At a deeper level, BG1 reflects Pudu’s modern interpretation of inventor spirit. Real inventors do not just make complexity for its own sake. They question the problems the industry has accepted for too long. They are willing to rebuild from the bottom up. For large cleaning equipment, BG1 does not offer a compromise. It offers reconstruction. That takes both technical strength and the patience to invest in what is not immediately visible.
06 Defining the Future by Redefining the Standard
The BG1 Series represents a shift in how cleaning robots are defined.
While much of the industry still focuses on hardware specifications, BG1 emphasizes higher-level capabilities: environmental understanding, autonomous decision-making, and human-centric operation. Its AI computing platform and AI Magic Cleaning system provide a continuously adaptive intelligence, supported by a more capable and responsive physical design.
For Pudu Robotics, BG1 marks a key milestone—from automation to intelligence, and now to AI-native systems. For users, it evolves from a machine into a system that adapts and improves with use. As AI-native capability becomes a new benchmark, competition is shifting from parameters to system-level intelligence—signaling the start of a new technological paradigm.
According to the Frost & Sullivan Global Commercial Service Robotics Market Report (2023), Pudu Robotics ranks first globally with a 23% market share. Its cleaning portfolio has become a major growth driver, contributing over 70% of total revenue in 2025 and reinforcing its leadership in the global commercial cleaning robotics market.
About Pudu Robotics
Pudu Robotics, a global leader in the commercial service robotics sector, is dedicated to empowering easier work and better lives through AI and robotics, with a vision of building a global intelligent robotics infrastructure that serves 10 billion people worldwide.
Built on three core technologies—mobility, manipulation, and AI—Pudu Robotics has pioneered an industry-first “One Brain, Multiple Embodiments” architecture, establishing a comprehensive product portfolio that includes specialized, semi-humanoid, and humanoid robots.
Currently, Pudu offers four major product lines: service delivery, commercial cleaning, industrial delivery and general embodied AI. Its solutions are widely deployed across industries such as retail, hospitality, manufacturing and industrial facilities, food and beverage, real estate and property services, healthcare, entertainment and sport, education, and public services.
To date, Pudu Robotics has shipped over 120,000 units globally, with a presence in more than 80 countries and regions.
