Simultaneous Localization and Mapping (SLAM) is the key technology to achieve autonomous localization of mobile robots in an unknown environment. The core idea of SLAM is to use the current map, which has already been established for robot localization, and then to update the current map with the new pose of the mobile robot. The intelligent mobile robot is a kind of robot with self-planning, self-organization, and self-adaptive ability working in a complex environment. The purpose of smart navigation is to make the robot move purposefully and complete specific tasks and perform particular operations without human intervention.
The global Simultaneous Localization and Mapping (SLAM) technology market expected to bolster the market growth with USD 500 million at an anticipated CAGR in the forecast period from 2020-2027. To solve the problem of accurate navigation, and detection of the autonomous underwater vehicle (AUV) and map construction algorithm based on inertial sensors and sonars are deriving the market growth of the global SLAM technology.
The SLAM algorithm integrates the data collected from various sensors (such as lidar, inertial measurement units, and cameras) to calculate the position of the sensor and draw a map around the sensor. With the development of artificial intelligence technology, it is conceivable that smart devices with simultaneous positioning and mapping functions will play a significant role in future lives.
Moreover, the simultaneous localization and mapping (SLAM) technology refer to the use of robots or uncrewed vehicles to navigate the environment where no prior signal is available. It is a beneficial and useful technology for a driverless car that creates a 3D mapping from surrounding and roof-mounted LIDAR sensors.
Furthermore, With the development of science and technology, people’s living standards have improved. People want the machine to be more intelligent so, it can free people from those heavy work. Early robots could only follow a predefined program and complete a single task. A genuinely autonomous robot should have a primary function that it can locate itself in the environment. It requires the robot to draw the map of the situation and find it on the map. This function is the task of Simultaneous Localization and Mapping (SLAM).
Visual SLAM technology used to provide precise location and positioning of indoor. It is one of the complex processes that calculate the real-time position of the device by sending visual inputs from a camera and simultaneously mapping the environment. Therefore, visual SLAM technology helps in providing real-time mapping and pictures of the environment where the GPS signal is not there.
Augmented reality help in the growth of SLAM by not only creating and update a map of the surrounding environment in real-time but also accurately estimate the position and orientation of the mobile phone camera relative to the map. This technology has always been a significant challenge in the field of computer vision and robot research, that is, Simultaneous Localization and Mapping (SLAM).
Based on the offering, the global simultaneous localization and mapping technology market attributed to 2D SLAM, 3D SLAM. The 2D SLAM segment accounted for the largest share of the simultaneous localization and mapping technology market is expected to grow at a bolster rate during the forecast period from 2020-2027. It is mainly owing to the adoption of domestic robots used for effective navigation and localization. Therefore, 2D SLAM technology is fueling the market share for the global simultaneous localization and mapping technology market.
Based on the type, the global simultaneous localization and mapping technology market classified into EKF SLAM, Fast SLAM, Graph-Based SLAM, LSD SLAM, S-PTAM, ORB-SLAM, and ORB-SLAM2. The Fast SLAM has the largest market share in the global simultaneous localization and mapping technology market. It is mainly owing to the adoption of Fast SLAM as it is an algorithm for autonomous capable of navigation of mobile devices. Also, the growing demand for domestic robots increases the penetration of mapping technologies. Therefore, Fast SLAM used to support the penetration by refining the accuracy of mapping and localization and improve compact hardware requirements.
Based on the Application, the simultaneous global localization and mapping technology market segmented into Robotics, UAV, AR/VR, Automotive. The AR/VR segment has emerged the market share of the global simultaneous localization and mapping technology market and expected to dominate in the forecast period as well. It mainly owes to provide better user experience, and advancement in SLAM technology has fueled the market demand for augmented reality and visual reality. Moreover, improving cloud service facilities, improving mapping accuracy are raising the demand for AR/VR in SLAM technology.
Based on geography, the global simultaneous localization and mapping technology market segmented into North America, Europe, Asia Pacific, South America, and Middle East & Africa. North America expected to hold the largest share of the global simultaneous localization and mapping technology market. Due to rising technology advancement, increasing disposable income emerges the demand for the adoption of domestic robots. Thus, North America will bolster the market share of the simultaneous localization and mapping technology in the forecast period as well.
Companies such as Intel, Microsoft, Alphabet, Amazon Robotics, Apple, Clearpath Robotics, Aethon, The Hi-Tech Robotic Systemz, Facebook, Intellias, Magic Leap, Rethink Robotics, Skydio, NavVis, MAXST, and Mobile Industrial Robots ApS and others are key players in the global simultaneous localization and mapping technology market.