What is taken into account when planning a route for a cleaning robot?
Modern cleaning technologies increasingly rely on route planning, which allows for the effective automation of the cleaning process. In large shopping centers, office buildings, warehouses, and medical facilities, navigation for robots is not just a convenient feature, but a key factor in reliable and effective cleaning.
In this article, we will examine how robots orient themselves in space, what is included in the concept of a “cleaning map,” and what parameters are critical when planning a route.
In this article, we will examine how robots orient themselves in space, what is included in the concept of a “cleaning map,” and what parameters are critical when planning a route.
Why route planning is the basis of “smart” cleaning
Without a clear route, even the most advanced robot loses its effectiveness. A properly designed cleaning map allows you to:
minimize navigation time;
avoid repeating the same area;
take obstacles and passageways into account;
optimize battery and cleaning product consumption;
ensure consistent results without staff intervention.
Thus, route planning is the basis of smart cleaning, in which the device does not act chaotically, but strictly according to a set logic.
minimize navigation time;
avoid repeating the same area;
take obstacles and passageways into account;
optimize battery and cleaning product consumption;
ensure consistent results without staff intervention.
Thus, route planning is the basis of smart cleaning, in which the device does not act chaotically, but strictly according to a set logic.
How robots navigate indoors: key technologies
Before we move on to route planning, let's take a look at how robots navigate and what technologies help them understand where they are.
Key navigation elements:
Lidars (laser rangefinders) — create a three-dimensional model of the room in real time.
3D cameras — allow objects to be recognized and even classified (for example, distinguishing a glass partition from a wall).
Inertial modules — track the robot's movements and turns.
Routers and beacons — used in large facilities where GPS and Wi-Fi do not work reliably.
Collision sensors — help avoid accidents.
Based on all this data, the robot builds a navigation map that is constantly updated.
Before we move on to route planning, let's take a look at how robots navigate and what technologies help them understand where they are.
Key navigation elements:
Lidars (laser rangefinders) — create a three-dimensional model of the room in real time.
3D cameras — allow objects to be recognized and even classified (for example, distinguishing a glass partition from a wall).
Inertial modules — track the robot's movements and turns.
Routers and beacons — used in large facilities where GPS and Wi-Fi do not work reliably.
Collision sensors — help avoid accidents.
Based on all this data, the robot builds a navigation map that is constantly updated.
What is taken into account when planning a route: a detailed analysis
1. Room geometry and area
The first and most important factor is the exact dimensions of the room, the width of the passageways, the presence of corners, turns, bottlenecks, and dead ends. Route planning should take into account:
the width of passageways;
the number of rooms or areas;
total area and accessible areas (areas with permanent obstacles are excluded).
2. Objects and obstacles
The cleaning map should indicate:
furniture and stationary structures;
temporary obstacles (e.g., boxes, carts, people);
glass, mirror, and transparent partitions.
Modern robots can even take moving objects into account, bypassing them and returning to the interrupted route.
3. Zoning and priorities
Premises are divided into zones:
high traffic (hallways, corridors, reception areas);
medium contamination (offices, wards);
sensitive areas (laboratories, operating rooms).
The planning system can assign different cleaning frequencies and depths for each zone.
4. Type of flooring and cleaning requirements
Some floors require only dry cleaning, others require wet cleaning. There may also be areas that require:
polishing;
antibacterial treatment;
intensive cleaning (e.g., a storage area with oil spills).
The route must take into account the type of cleaning for each specific area.
5. Level of autonomy and battery charge
Modern robots analyze:
charge level;
availability of a base station nearby;
path to the recharging area without interruptions.
If the route is too long, it is automatically divided into logical blocks.
1. Room geometry and area
The first and most important factor is the exact dimensions of the room, the width of the passageways, the presence of corners, turns, bottlenecks, and dead ends. Route planning should take into account:
the width of passageways;
the number of rooms or areas;
total area and accessible areas (areas with permanent obstacles are excluded).
2. Objects and obstacles
The cleaning map should indicate:
furniture and stationary structures;
temporary obstacles (e.g., boxes, carts, people);
glass, mirror, and transparent partitions.
Modern robots can even take moving objects into account, bypassing them and returning to the interrupted route.
3. Zoning and priorities
Premises are divided into zones:
high traffic (hallways, corridors, reception areas);
medium contamination (offices, wards);
sensitive areas (laboratories, operating rooms).
The planning system can assign different cleaning frequencies and depths for each zone.
4. Type of flooring and cleaning requirements
Some floors require only dry cleaning, others require wet cleaning. There may also be areas that require:
polishing;
antibacterial treatment;
intensive cleaning (e.g., a storage area with oil spills).
The route must take into account the type of cleaning for each specific area.
5. Level of autonomy and battery charge
Modern robots analyze:
charge level;
availability of a base station nearby;
path to the recharging area without interruptions.
If the route is too long, it is automatically divided into logical blocks.
- How a cleaning map is created: stages
- A cleaning map is created in several stages:
- Stage 1: Initial reconnaissance
- After being turned on, the robot scans the room using lidars and cameras, determining boundaries, objects, and obstacles.
- Stage 2: Digital map formation
- Based on the collected data, a digital model of the space is formed, including:
- walls, corners, entrances;
- permanent objects (tables, partitions);
- restricted access areas.
- Stage 3: Zone configuration
- The operator sets the following in the interface:
- working and non-working zones;
- cleaning frequency;
- types of tasks (dry, wet cleaning).
- Stage 4: Route optimization
- AI algorithms analyze the map and select the optimal route, taking into account:
- the shortest paths;
- avoidance of repetitions;
- minimum number of turns and U-turns;
- maximum logistical efficiency.
- Intelligent planning algorithms: how they work
- Modern robots use AI for navigation, which is constantly learning. Machine learning algorithms allow them to:
- adapt the route when the furniture layout changes;
- adjust to the “human factor” — open doors, people passing by;
- analyze route efficiency based on previous runs.
- This kind of intelligence in cleaning allows you to not just follow a set path, but to flexibly manage the process in real time.
- Examples of non-standard routing scenarios
- Medical facility: the robot works at night, avoids patient rooms, and cleans on a schedule.
- Shopping center: peak attendance is taken into account, and the route is adapted according to the time.
- Warehouse: the robot works in narrow aisles between shelves, reacting to pallets and carts.
- Open space office: recognizes work areas, avoids wires and chairs.
Common mistakes when planning routes
Lack of an accurate map of the premises.
Incorrect zoning.
Ignoring the charging station when planning the route.
Unaccounted obstacles (e.g., new partitions).
Lack of analysis of previous runs.
To avoid mistakes, it is always recommended to use cloud-based route planning, where you can quickly edit the map and tasks.
Advantages of an intelligent route
✅ Reduced cleaning time
✅ Improved quality
✅ Minimized failures
✅ Maintained stable schedule
✅ Flexibility in case of changes
Lack of an accurate map of the premises.
Incorrect zoning.
Ignoring the charging station when planning the route.
Unaccounted obstacles (e.g., new partitions).
Lack of analysis of previous runs.
To avoid mistakes, it is always recommended to use cloud-based route planning, where you can quickly edit the map and tasks.
Advantages of an intelligent route
✅ Reduced cleaning time
✅ Improved quality
✅ Minimized failures
✅ Maintained stable schedule
✅ Flexibility in case of changes
Conclusion: navigation as the key to effective cleaning
Route planning is not just a technical task, but a strategic process that directly determines the effectiveness of the entire robotic cleaning system. It is precisely competent navigation that allows the robot to determine as accurately as possible how it orients itself in space, avoiding obstacles, taking into account people's movement patterns, and automatically selecting the optimal trajectory.
Modern technologies, including lidars, 3D cameras, SLAM algorithms, and artificial intelligence, allow you to build dynamic cleaning maps adapted to the real situation at the facility. This is especially important in high-traffic environments: shopping malls, warehouses, airports, and other large spaces with heavy traffic.
Automatic route planning saves not only resources but also time: instead of static cleaning patterns, the robot responds to changing conditions, repeats cleaning in particularly dirty areas, and skips areas that do not need servicing. This approach allows you to maintain a stable level of cleanliness at minimal cost.
Every year, intelligent algorithms are becoming more accurate, and robot navigation is becoming more reliable and “human-like.” This opens up prospects for deeper automation and the introduction of robots even in rooms with complex geometry and variable conditions. Therefore, when choosing equipment and developing an implementation strategy, special attention should be paid to routing and adaptive navigation capabilities.
Thus, the answer to the question “how does a robot navigate” is a whole complex of factors: from the type of sensors to the quality of the software. And the more accurate the routing system, the higher the productivity, efficiency, and safety of the robot. This means that the contribution to the overall quality of cleaning becomes tangible and stable.
Conclusion: a properly constructed route is the key to effective and safe operation. This is the foundation on which any intelligent cleaning map is built, whether it is for an office, warehouse, or sales floor. And if you are planning to implement robotic technology, be sure to pay attention to the navigation system — the result of the entire automation process depends on it.
Route planning is not just a technical task, but a strategic process that directly determines the effectiveness of the entire robotic cleaning system. It is precisely competent navigation that allows the robot to determine as accurately as possible how it orients itself in space, avoiding obstacles, taking into account people's movement patterns, and automatically selecting the optimal trajectory.
Modern technologies, including lidars, 3D cameras, SLAM algorithms, and artificial intelligence, allow you to build dynamic cleaning maps adapted to the real situation at the facility. This is especially important in high-traffic environments: shopping malls, warehouses, airports, and other large spaces with heavy traffic.
Automatic route planning saves not only resources but also time: instead of static cleaning patterns, the robot responds to changing conditions, repeats cleaning in particularly dirty areas, and skips areas that do not need servicing. This approach allows you to maintain a stable level of cleanliness at minimal cost.
Every year, intelligent algorithms are becoming more accurate, and robot navigation is becoming more reliable and “human-like.” This opens up prospects for deeper automation and the introduction of robots even in rooms with complex geometry and variable conditions. Therefore, when choosing equipment and developing an implementation strategy, special attention should be paid to routing and adaptive navigation capabilities.
Thus, the answer to the question “how does a robot navigate” is a whole complex of factors: from the type of sensors to the quality of the software. And the more accurate the routing system, the higher the productivity, efficiency, and safety of the robot. This means that the contribution to the overall quality of cleaning becomes tangible and stable.
Conclusion: a properly constructed route is the key to effective and safe operation. This is the foundation on which any intelligent cleaning map is built, whether it is for an office, warehouse, or sales floor. And if you are planning to implement robotic technology, be sure to pay attention to the navigation system — the result of the entire automation process depends on it.
