LiDAR SLAM: what it is and how to eat it
August 09, 2022
SLAM - Simultaneous Localization and Mapping - is a process, or simply, a collection of algorithms in a sensor in a moving body (a robot, car, or drone) that maps an environment without prior information about it, while keeping track of its own location. LiDAR, in the other hand, is a sensor that detects objects and measures distance to them using light rays and measuring the time that it takes for them to reach an object and come back. Together, they make an excellent couple! in this article, we will try to brief you on LiDAR SLAM, its difference from GNSS and Visual SLAM, and how it can be used in different industries. Let’s dive in!
Localisation: GNSS vs SLAM
SLAM is often described as an alternative to a widely-used navigation system - Global Navigation Satellite System (GNSS). GNSS provides an accurate absolute positioning on Earth by using a constellation of satellites. However, it is not always precise and available in environments such as tunnels, caves, etc. Additionally, GNSS won’t be able to provide mapping, which is crucial in some scenarios. In such circumstances, accurately mapping an environment and navigating in it safely is achieved using SLAM. Mobile robots equipped with SLAM can be used in mining exploration, sea analysis, search and rescue, tunnel inspection, and so on. Main differences between GNSS and SLAM are summarized in the figure below:
Mapping: Visual SLAM vs LiDAR SLAM
LiDAR SLAM is a navigation process that uses a LiDAR sensor as a means of environment perception and surrounding data collection. “Why not use visual SLAM?”, one may ask.
Visual SLAM (vSLAM) methodology adopts video cameras to capture the environment and construct a map using different ways, such as image features (feature based visual-SLAM), direct images (direct SLAM), colour and depth sensors (RGB-D SLAM), and others. One of the biggest challenges that researchers face when dealing with visual SLAM is the performance of robots in conditions with varying lighting and weather.
LiDAR, on the other hand, is a sensor that can successfully operate and obtain 3D point clouds that can be easily interpreted to perform SLAM regardless of illumination levels or weather conditions. Thus, LiDAR SLAM is the choice, when factors such as lighting and climate are present in the picture.
Today, LiDAR SLAM is the prime component of mapping systems dynamically, without the need of complex and heavy hardware setups. It saves resources (human, time, costs), and gives an opportunity to create mapping of an area beyond human reach. Kodifly has started to extensively utilise LiDAR sensors in the projects to bring value to its customers through innovation, impeccable expertise, and long-term impact. Respective use cases include railway localisation, passenger safety, intrusion detection, to name a few.
How can LiDAR SLAM address industry needs?
Having a technical description of LiDAR SLAM is good, but mentioning actual applications with real impact is better. So, how can LiDAR SLAM address the industry needs?
- SLAM for indoor operations automation. Automated inspection of large indoor environments requires vehicles to localise accurately within space, while building 3D maps of the infrastructure. LiDAR SLAM is the favorable approach, being able to conduct building inspection with high level of detail, depth, and high resolution. With the boom of e-commerce, many warehouses decide to automate their operations by incorporating automated fleet management. Robots and drones need localisation software to be aware of their surroundings while navigating in indoor environments such as warehouses, plants, etc. Kodifly can provide that.
- SLAM for surveying and mapping. Use cases for this SLAM application are infinite. In agriculture, SLAM-enabled drones collect data on stock volume & vegetation density for better monitoring. In safety & security industry, SLAM UAVs can be used to detect threats and intrusion. In construction industry, SLAM is used for BIM, helping at every stage of project lifecycle. In mining and tunnels, SLAM can replace GNSS to monitor infrastructure conditions and detect changes. Kodifly can provide the required software and customize it for application-specific needs.
- SLAM for Smart City. In the context of Smart Cities, SLAM is useful when integrated with IoT devices that can collect and process point cloud data to create city maps. City maps which are useful for any smart city project involving traffic management, crowd control, and environment preservation. Kodifly can contribute to the Smart City development by providing SLAM-enabled LiDAR sensors and Video Analytics Solutions.
Individual problems require individual solutions. If you feel like your use case is different from what we have covered, don’t hesitate to let us know. We will be able to propose a tailor-made solution based on your goals and application needs, to eliminate your operational hurdles and increase process efficiency.
In this article, we try to brief you on LiDAR SLAM, its difference from GNSS and Visual SLAM, and how it can be used in different industries.
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