Robot vacuum cleaners roam around in your homes while picking up dust, dirt, debris, pet hair and more without any hassle. A question arises in most of the people’s minds is that how a robotic vacuum cleaner navigates or find its way or always know where to go? It’s a mystery for many people and some of them remain in continuous search to find an exact answer of this. Here in this article, we will try to explain how robotic vacuum cleaners navigate in homes effectively.
A robot vacuum cleaner navigates with the help of combination of different sensors; it uses various sensors to detect and measure the world around it.
A robot vacuum cleaner performs any task with the help of different sensors and the corresponding sensors that help the robotic vacuum in navigational tasks:
Detecting close obstacles
Mechanical Bumper: It’s a large contact-sensing mechanical bumper that is mounted on the front half of robot vacuum. This mechanical bumper sensor enables a robot vacuums to sense when they have bumped into an obstacle. After that, the robot vacuum cleaner will turn around or change its path accordingly.
Proximity sensors: It’s a type of sensor(either ultrasound or infrared) which can detect the presence of nearby object within a given distance, without any physical contact.
To create customize area
Magnetic sensors: This sensor is used to detect magnetic strip that is laid on the floor surface to set No Go area for robot vacuum.
Localization and mapping
Wheel encoders: They are used to determine the position of the wheels so they can improve the localization of robot vacuums.
Navigation system is the most advanced and critical feature in robot vacuum cleaners. This feature enables robot vacuums to sense and map their environment to move around in your home efficiently. SLAM( simultaneous localization and mapping) system of a robot vacuum cleaner determines the orientation and position of a vacuum by creating a map of their environment while simultaneously tracking the robot vacuum within that environment. SLAM system works with the help of optical sensors, if you want to know further about how robotic vacuum cleaner navigate then read the following article SLAM
According to different types of sensors, SLAM is mainly categorized into Visual-based SLAM( VSLAM) and laser SLAM.
What is Laser SLAM?
At present, Laser SLAM is the most secure, reliable and mainstream positioning and navigation method. Laser SLAM is a laser based navigation method, It points a laser at various obstacles, items, objects, and spaces that surround a particular device and then using that laser it construct a map of the space. The constructed map then enables the device to understand the space that it is working in. After understanding what is in the space, the device can operate in an efficient manner.
What is VSLAM?
With the passage of time, VSLAM has been given more importance because it collects large of data points, as a result, it provides large amount of information and wide scope of application.
VSLAM relies not only on lasers, but it also relies on camera too. The camera allows a particular device to create visual images of a particular space. After putting all of the images together, VSLAM enables the device to map the space, this includes all the obstacles, objects and items within the space, which helps the device to navigate conveniently.
Laser SLAM vs VSLAM
The following is a comparison between VSLAM and Laser SLAM in various aspects.
VSLAM mainly collects data information through cameras and the required cost of cameras is normally not much high. Whereas, Laser SLAM uses laser to construct a map of the space and the cost of laser SLAM is relatively high as compared to VSLAM. However, laser SLAM can measure the angle and distance of the object points with high accuracy, making the device efficient in positioning and navigation.
Laser SLAM accuracy is higher than VSLAM in constructing a map of the surrounding. Moreover, the laser SLAM can be directly used for positioning and navigation.
VSLAM has much higher scope of application. VSLAM technology can work indoor and outdoor environment conveniently, however it is highly dependent on light and can’t perform in the dark or in some textured areas.
Ease of usability
Laser SLAM and VSLAM with depth cameras directly get environment data via data in cloud. The robots can predict and measure the distance of objects and where they are in the space. Nonetheless, the VSLAM scheme which is based on monocular, binocular, and fish-eye camera can’t directly get environment data in clouds but it forms gray or color images.
- It provides extractable semantic information
- There is no limit on sensor’s distance detection range
- Low cost is required
- The structure of VSLAM is simple and the installation mode is diversified
- It doesn’t work in dark or in some textured areas
- It requires heavy load in computing and the constructed map itself is difficult to be directly used in path planning and navigation.
Laser Slam advantages
- Laser SLAM is more reliable and mature technology than VSLAM
- The map constructed by Laser SLAM is based on intuitiveness and the precision is high. Furthermore, there is no cumulative error
- The maps of laser SLAM can be used for path planning
Laser Slam disadvantages
- Laser SLAM is limited by LIDAR detection range
- Laser SLAM maps lack semantic information
- Laser SLAM requires installation with structural requirements
Laser SLAM and VSLAM both are fantastic navigation systems. One of these systems is better for you than the other, the navigation system you are looking for depends on the accuracy that you require and your budget.