The global simultaneous localization and mapping (SLAM) technology market size was valued at USD 226.7 million in 2021. It is expected to reach USD 9,425.7 million by 2030, growing at a CAGR of 49.41% during the forecast period (2022–2030).
Simultaneous Localization and Mapping (SLAM) is a type of technology used in computer vision systems that collect visual information from the outside world using a variety of built-in sensors. By converting this data into a different format, SLAM technology makes it simpler for machines to comprehend and interpret it using visual cues. Before the development of SLAM technology, it was difficult for indoor devices to localize themselves in their surroundings and understand the map of their operating environment. This issue was known as the "chicken and egg" problem because localization required surrounding area maps, and surrounding area maps required localization. The SLAM technology simultaneously addresses the localization and mapping issues and provides a solution to this chicken-and-egg issue.
In augmented reality, SLAM technology has established itself as a game-changing innovation. Simultaneous Localization and Mapping technology's many benefits, including greater accuracy and increased efficiency, are gradually replacing marker-based technology. In marker-based technology, to experience augmented reality, a defined image needs to be placed in front of the device's camera. The requirement to create an image to experience augmented reality presented the most significant difficulty with marker-based AR. Since SLAM-based AR uses sensors to precisely detect the real-world environment, this issue has been solved. As a result, AR companies are now implementing SLAM technology, which is anticipated to help their demand growth over the forecast period.
Increasing Demand for Service Robots in Domestic Use
The market for service robots has accelerated due to the rising demand for robots in various industries, including logistics and warehouse, defense and security, agriculture, public relations, healthcare, entertainment, and household. Additionally, one of the critical elements promoting the development of these robots in the market is the rising level of consumer awareness. A sizeable portion of the need for service robots is made up of robots used in domestic settings. Integrating autonomous capabilities into domestic and household robots is extremely difficult. Due to the chaotic environment of households, procedures are becoming more complex. In this sense, the robots' ability to localize their positions and map their surroundings is made possible by SLAM technology. For better autonomous operation, SLAM technology is now being used by several domestic robot manufacturers. For instance, the Roomba cleaning robots produced by iRobot Corporation use SLAM technology to map out the house and clean it efficiently while acting autonomously.
One of the players' most significant challenges is the technical complexity of applying SLAM technology. The application of SLAM technology presents various intricate challenges, whether in robotics, UAVs, self-driving cars or augmented reality. The blurring effect and difficulty detecting loop closers in robotics are some of the most significant technical challenges. In addition, the technology is still in the early stages of development and testing, and difficulties have not yet been thoroughly investigated. The high investment is a significant barrier to SLAM technology's wider adoption. Therefore, it is difficult for small and medium enterprises to adopt SLAM technology (SME) robots. The added cost associated with SLAM technology in UAV applications deters UAV operators from purchasing SLAM technology-based UAVs. Therefore, the main obstacles to expanding the global SLAM technology market are the technical complexity and high setup cost.
Sensors, processors, AI, and machine learning have recently improved UAV technology. UAV technology developers are designing AI-based collision avoidance systems that take prompt action in case of BVLOS obstacle detection. Iris Automation tested its AI-based collision avoidance technology in over 7000 flights. Integrating advanced technologies like AI-powered sense-and-avoid systems into drones increases their automaticity and BVLOS range. Currently, commercial end users are restricted from operating drones in BVLOS, but these restrictions are expected to ease, causing the market for BVLOS drones to explode in the next five years. SLAM technology detects the environment for such drone operations, which is anticipated to drive market growth.
Self-driving cars and autonomous vehicles are seen as the mobility of the future. These vehicles operate based on sensing their immediate environment and moving with the slightest assistance. The development of autonomous vehicles is pursued by several major global automotive companies, including Tesla, Google, Uber, Mercedes-Benz, General Motors, Continental Automotive Systems, Autoliv Inc., Bosch, Nissan, Toyota, Audi, and Volvo. Google's Waymo self-driving car program utilizes SLAM technology for independent movement. This technology builds a map of the area around the car as it moves using data from LiDAR and other sensors. By boosting autonomy and lowering the chance of error, the SLAM technology used in self-driven cars improves accuracy and overall performance. The opportunities for the global SLAM technology market during the forecast period consequently grow.
The global simultaneous localization and mapping (SLAM) technology market is segmented by mapping, type, platform, and end-user.
Based on the mapping, the global SLAM technology market is bifurcated into 2D SLAM and 3D SLAM.
The 2D SLAM segment is the highest contributor to the market and is expected to grow at a CAGR of 46.79% during the forecast period. Most hardware components in 2D SLAM use 2D sensors for mapping, localization, and motion planning. The 2D SLAM method is based on a laser scanner. These systems take frames, extract 2D measurements and data points, and create 2D maps. For robots and autonomous vehicles moving in a 2D plane, 2D SLAM is sufficient. Compared to 3D SLAM, 2D SLAM is simpler to implement and less complex.
Simultaneous localization and mapping in three dimensions are referred to as 3D SLAM. These systems make it possible for robotic systems to navigate in three dimensions. Higher-level robotics systems, drones, and augmented reality applications are the primary users of 3D SLAM solutions. Comparatively speaking, these solutions are computationally more complex than 2D SLAM.
Based on the type. the global SLAM technology market is bifurcated into extended Kalman filter (EKF), graph-based SLAM, and fast SLAM.
The Kalman filter segment is the highest contributor to the market and is expected to grow at a CAGR of 46.41% during the forecast period. Extended Kalman filter (EKF) SLAM is one of the proposed solutions to the online SLAM problem. The robot's current position is estimated without considering its entire trajectory path in an online SLAM problem. In this method, the robots' mounted sensors are used to locate the landmarks. As the computation system cannot map a larger number of landmarks in real-time, this is regarded as unsuitable for missions lasting a long time. Robotic mapping and autonomous vehicles are examples of applications where EKF SLAM has been used for more than 20 years and is still being used.
In graph-based SLAM, robot poses and landmarks are represented by nodes, while edges represent constraints between the poses. Following the creation of such a graph, the computation of the map is initiated by examining the spatial arrangement of the nodes. The first step in optimizing a chart is forming a new map by correcting node information.
Based on the platform, the global SLAM technology market is bifurcated into robots, UAVs, augmented reality, and autonomous vehicles.
The robots segment owns the highest market share and is expected to grow at a CAGR of 35.50% during the forecast period. Robots that operate on SLAM technology can move independently. Due to SLAM technology, robots can simultaneously gather information about their surroundings, track their position, and create live maps of their surroundings in real-time. Robots used in industry, cleaning, and security primarily employ SLAM technology. The robotics industry has enormous potential for SLAM technology, which has many uses. These possibilities have inspired numerous robotics companies to collaborate on technological advancement. Thus, SLAM technology for robotics offers previously unheard-of options in the future.
Unmanned aerial vehicles (UAVs) are autonomous or partially autonomous platforms for various tasks, including delivery, surveillance, and inspection. UAVs use SLAM technology to map their surroundings. The UAVs have an additional SLAM module that allows them to map and localize their surroundings simultaneously. The market for SLAM technology in the world for UAVs currently has the second-highest share. The high sector growth and extensive R&D efforts made by the SLAM technology's developers to be integrated into drones are credited for this sizeable share.
Based on the end-user, the global SLAM technology market is bifurcated into manufacturing and logistics, commercial, household and military.
The manufacturing and logistics segment is the highest contributor to the market and is expected to grow at a CAGR of 34.20% during the forecast period. Robots have been utilized extensively in the manufacturing sector for quite some time. However, as technology develops, better solutions are being considered. The leading candidate to eventually replace other navigation technologies is SLAM technology. Additionally, the expanding e-commerce sector is a significant driver of the demand for logistics robots because they can perform various tasks. Other industries have adopted robots in their logistics and warehouse centers due to automation's benefits. Robots can carry out multiple tasks necessary for warehouse and logistics operations, helping the sectors save time and money. As a result, more businesses are implementing SLAM technology to boost the efficiency of their robots.
The commercial end-user market has significantly increased UAV sales over the past few years. Due to the rising demand for UAVs for various commercial applications, numerous startups are entering the market. Drones used for photography and recreational activities are among the UAVs that have applications in homes. In the manufacturing industry, UAVs are used mainly in assembly-line inspection procedures. Due to the growing need for surveillance and intelligence gathering, there is a greater demand for drones in the defense sector.
Europe Dominates the Global Market
By region, the global simultaneous localization and mapping (SLAM) technology market is segmented into North America, Europe, Asia-Pacific, and Rest of the World.
Europe is the largest shareholder in the global simultaneous localization and mapping (SLAM) technology market and is expected to grow at a CAGR of 48.96% during the forecast period. One of the leading nations in Europe, Germany is heavily invested in advancing SLAM technology for various uses. Robots and unmanned aerial vehicles (UAVs) are two products heavily researched in Germany for potential SLAM applications. Germany currently holds the largest market share for SLAM technology in all of Europe. It is predicted to maintain its dominance by 2030, followed by France, Germany, the United Kingdom, and the rest of Europe.
North America is expected to grow at a CAGR of 47.62%, generating USD 2,727.4 million during the forecast period. Regarding market share, North America currently ranks second in the SLAM technology sector. Many robotics, drone, and augmented reality businesses in North America are emerging, and established companies are growing. In North America, the SLAM technology is applied to various industrial, domestic, commercial, military, and logistical applications. Demand for industrial and logistics robots across multiple industries is one of the main drivers of SLAM technology demand among regional commercial end users.
One of the most lucrative markets in the world is Asia-Pacific (APAC). The capital spending on industrial automation is aggressively rising in the Asia-Pacific region. China, Japan, India, and South Korea are the principal contributors to the expansion of the robotics industry in the Asia-Pacific region. As the demand for SLAM-based robots, UAVs, and augmented reality platforms rises for both commercial and non-commercial applications, there are numerous opportunities for new entrants in this field. Additionally, there is active research for SLAM-based autonomous vehicle technologies in several Asia-Pacific nations. One of the key factors propelling the development of SLAM technology in Asia-Pacific is the rising commercial use of autonomous robots and drones among the APAC region's nations.
The Middle East and Africa (MEA) and Latin America are the most significant regions for SLAM technology in the rest of the world. The Middle East comprises several nations, including the United Arab Emirates, Saudi Arabia, Kuwait, Iran, Turkey, and Israel. Middle Eastern countries are actively involved in ongoing robotics industry developments to keep up with the rapidly evolving global robotics market. In order to improve their automation and robotics capacities, the nations are also working with Asia-Pacific nations.
List of key simultaneous localization and mapping (SLAM) technology market companies profiled
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