SLAM stands for “simultaneous localization and mapping”. It’s an acronym typically used to describe navigation technology in autonomous robots. “All SLAM solutions include some type of device or tool that allows a robot or other vehicle to observe and measure the environment around it. This can be done by cameras, other types of image sensors, LiDAR laser scanner technology, and even sonar.” (Source: Flyability.com) What makes a good and capable autonomous robot; is the quality of data and the capabilities of curated hardware.
SLAM Technology in Confined Spaces
However, not all SLAM is the same. SLAM is used for a variety of autonomous robot industry applications. When using SLAM technology in a confined space like an office, home, or pool, the robot is limited to the walls of that unique space. Some examples are the iRobot Roomba floor vacuum and the Dolphin robotic pool cleaner.
These robots may include navigational components, such as a “gyroscope” or other sensors to measure and calculate orientation. A gyroscope is kind of like a modern compass for a robot and is a component that can measure rotational speed and calculate rotational change. Combined with a computer and advanced algorithms, the robot can efficiently and effectively perform its cleaning role.
In autonomous robots SLAM allows the device or vehicle to map and track where it is in the home, backyard pool, large facility, or on an open road. Think of it as if you are blindfolded and someone opened a door into a room that you are now in. The question is “How are you going to understand where you are in this space, and map and track your movements while later knowing how to return to a previous spot?”
Image Sources: Maytronics Dolphin Robotic Pool Cleaners, iRobot Roomba, and Waymo Driverless Taxi’s.
SLAM technology allows autonomous robots to navigate with
precision. For instance, an iRobot Roomba not only cleans while its owner is at
work or enjoying their free time, but it can clean in more efficient patterns
than cleaning manually with a vacuum.
Similarly, robotic pool cleaners use algorithms to
methodically clean a pool’s floor, walls, and waterline in 2 hours with zero
missed spots. Whereas, a legacy pool cleaning technology (without SLAM technology)
will clean while roaming the pool in random patterns, leaving unclean spots
even after 4-8 hours of operation.
Image Source: Mathworks
SLAM Technology in Large Open Spaces
The size and nature of the space, and whether the space is contained will dictate how much technology needs to be added to improve the performance of the autonomous robot. For instance, a pool robot may only need a gyroscope and a few sensors, whereas a floor vacuum may need LiDAR, a camera, and other sensors to perform its tasks, while a car may need much more advanced components, plus GPS.
One of these common technologies is LiDAR. LiDAR stands for “light detection and ranging”. LiDAR is a device that is similar in operation to radar but emits pulsed laser light instead of microwaves. LiDAR supports autonomous driving and navigation by using artificial intelligence to recognize unusual shapes and avoid unidentified objects (Source: Merriam-Webster). [Learn more about “What is LiDAR?”]
When referring to the use of SLAM in a large facility, autonomous robots may be confined to a floor or several larger areas. An example of this is the ADIBOT A1 fully autonomous UV-C disinfection robot. These types of robots tend to have longer battery life, greater range, and the ability to recharge themselves – all upgrades a robot with this type of role needs to be efficient and effective with this larger scope of work.
All sensing tech has weaknesses, robots running into glass with only lidar, latency processing importance, and busy environment implementation challenges. This is why the ADIBOT A1 deploys so many to build on each other and ensure redundancy, capability, adaptability, and immediacy.
When the size of the space significantly increases, people and other moving devices are added to the space, the autonomous robot requires additional components to improve mapping, cleaning, localization, safety, depth perception, and obstacle avoidance.
Infographic Source: Ouster
SLAM Technology in a Fully Open Environment
The application of SLAM in an autonomous car must account for travel in the open. An example of this is the Waymo driverless taxi. When driving on the open road, SLAM technology needs to be significantly improved with additional sensors, LiDAR, cameras, safety features, and obstacle avoidance. Then it must flawlessly perform without any glitches or the need to reboot the vehicle’s computer – all while constantly knowing its precise location on the road and the street map.
IMUs stand for “inertial measurement units”. In an autonomous vehicle, IMUs provide three-dimensional and angle rate measurements. This helps the navigation system process raw data and make better decisions on movement and position (Source: Inertiallabs.com).
Navigation systems for autonomous vehicles are state of the art and utilize this raw data from gyroscopes, LiDAR’s, cameras, GPS, and sensors continuously – constantly adjusting and making driving decisions with the ability to avoid potential risks to the passengers within milliseconds.
Image Source: Dioram
The future of SLAM technology will be focused on improvements to performance and reliability, communication with other devices, and greater autonomy. In conclusion, autonomous robots will increasingly assist workers and customers, enhancing productivity and creating valuable synergies by handling various tasks efficiently.
Reference Sources:
What is simultaneous localization and mapping, https://www.flyability.com/blog/simultaneous-localization-and-mapping
IMU Kernal and their role in autonomous vehicles, October 2023, https://inertiallabs.com/imu-kernel-and-their-role-in-autonomous-vehicles/#:~:text=IMUs%20provide%20three%2Ddimensional%20acceleration,the%20vehicle’s%20movement%20and%20position.
