In the industrial context, mobile automation has become a significant competitive advantage. This innovation is made possible by a fundamental technology: SLAM, or Simultaneous Localization and Mapping.
This technology is especially used in Autonomous Mobile Robots (AMRs), but it is also present in other sectors, from drones to assisted surgeries. The major advantage is the accuracy and real-time updating of coordinates without the need for direct human intervention.
Understand how SLAM technology works in this article and how it can benefit your business!
The Concept Behind SLAM
Imagine a robot in a completely new environment, without pre-existing maps for guidance. In this scenario, the challenge is twofold: it must accurately determine its own location and create a detailed map of the environment as it progresses. This is where SLAM comes in.
It combines the real-time location of the robot with the gradual construction of a detailed map, enabling successful navigation in constantly changing or even unknown environments.
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The Pillars of SLAM: Mapping and Localization
SLAM is a complex interaction between two essential pillars: mapping and localization. Let's explore each one to understand how they work together, enabling precise autonomous navigation of AMRs.
Mapping
The mapping process in SLAM involves creating a detailed map of the environment where the robot operates. This is done by combining data from various sensors, such as cameras, LIDAR, IMUs, and encoders.
For example, LIDAR provides three-dimensional reference points to build a 2D or 3D map of the environment. These points are combined with visual information from cameras and motion data from encoders, forming a complete and highly accurate map.
Localization
Localization, on the other hand, is the robot's ability to determine its precise position on the under-construction map. This is achieved by comparing sensor data with existing map references.
As the robot moves, it continually compares sensory information with the map in real-time to calculate its current position. Filtering algorithms, such as the extended Kalman filter (EKF) or particle filter algorithms, often estimate the robot's position, considering sensor uncertainties.
SLAM Iterative Process
A captivating aspect of SLAM is its continuous iterative process. This means that the robot doesn't merely create a map and determine its location once; instead, it consistently updates and refines the map and location as it moves through the environment.
When the robot makes new measurements and observations, it compares that data with existing information on the map to enhance overall accuracy. This capability allows for the correction of accumulated errors and adjustments in perceptions when exploring different areas.
SLAM applications beyond navigation
SLAM extends beyond the autonomous navigation of mobile robots in logistics and manufacturing. It is employed in autonomous vehicles, drones, augmented reality, indoor and outdoor mapping, industrial inspections, and even robot-assisted surgery. This versatility underscores the power of SLAM as a tool that expands automation and robotic perception.
In the industry, the use of SLAM with AMRs revolutionizes the landscape. While Automatically Guided Vehicles (AGVs) are confined to predefined routes and static environments, AMRs equipped with SLAM operate in constantly changing environments.
The ability to deflect obstacles in real-time, create maps during movement, and adjust routes drives efficient cargo movement and adaptation to the environment.
ACTA: Innovation in Mobile Automation with SLAM Algorithm
In the Brazilian scenario, the company Acta Robotics has excelled in the development, manufacturing, and support of AMRs. With a highly qualified team, the company offers customized solutions to meet the unique needs of each client. Its AMRs are designed to operate safely in challenging environments, featuring cutting-edge technology that ensures efficiency, reliability, and scalability.
Recently, Acta Robotics joined forces with Venturus to provide customized solutions integrated into the operations of Brazilian logistics industries and companies. Together, they offer end-to-end solutions in the areas of robotics, computer vision, and artificial intelligence.
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