In this report, the market has been segmented based on type, technology, application and geography.The report provides an overview of the global SLAM market and analyzes market trends.
Using 2021 as the base year, the report provides estimated market data for the forecast period from 2022 through 2027.Revenue forecasts for this period are segmented based on type, technology, application and geography.
Market values have been estimated based on the total revenue of SLAM providers.
The report covers the market for SLAM with regard to the user base across different regions.It also highlights major trends and challenges that affect the market and the vendor landscape.
The report estimates the global market for SLAM in 2021 and provides projections for the expected market size through 2027.
The scope of the study includes SLAM and associated services, as well as services associated with the platform.
- 21 data tables and 10 additional tables
- An overview of the global market outlook for simultaneous localization and mapping (SLAM) technology
- Estimation of the market size and analyses of market trends, with data from 2022, estimates for 2023 and projections of compound annual growth rates (CAGRs) through 2028
- Highlights of the market potential for SLAM market by offering, type, application, and region
- Information on "chicken and egg" problem and discussion on how this problem can be resolved with the help of SLAM technology
- Coverage of macroeconomic factors of the SLAM market and impact analysis of COVID-19 and Russia-Ukraine War on SLAM
- Assessment of the market dynamics and key technological developments in SLAM technology, as well as identification of market trends, opportunities, and challenges affecting the market
- Market share analysis of the key companies of the industry and coverage of their proprietary technologies, strategic alliances, and other key market strategies
- Company profiles of major players within the industry, including Alphabet Inc., Amazon Robotics, Apple Inc., Clearpath Robotics Inc., and Intel Corp.
Computer vision systems use a technology called “simultaneous localization and mapping” (SLAM) to gather visual data from the outside world using a wide range of built-in sensors.SLAM technology transforms the collected data into a distinct format that is easier for machines to understand and interpret using visual cues.
Indoor devices had a hard time locating themselves in their surroundings and comprehending the map of their operational environment prior to the development of SLAM technology.Localization required surrounding area maps, and surrounding area maps required localization, so this problem was referred to as the “chicken and egg” problem.
This problem is resolved by the SLAM technology, which simultaneously addresses the localization and mapping concerns.
Increasing applications of SLAM technology in augmented reality (AR) applications, coupled with the rising demand for service robots from domestic applications (e.g., logistic warehouses, agriculture, households), along with the defense and security and government sectors, is boosting the market growth. The challenges in SLAM implementation, however, are currently hindering market growth. The emergence of autonomous vehicles and the growing demand for self-operating drones and beyondvisual-line-of-sight (BVLOS) operations are projected to provide new opportunities in the market, thereby enhancing future growth for SLAM.
The global SLAM market was estimated to be worth $REDACTED million in 2021.The market is projected to grow at a CAGR of REDACTED%, and it is forecast to reach $REDACTED billion by 2027.
The need for autonomous vehicles has been significantly driving the SLAM market.Major demand is from the UAVs industry, where these have been becoming popular for real-time mapping, monitoring and surveillance applications.
The loop closure issue, which must be solved using visual information in situations that last a lifetime due to dynamic elements, lighting, weather or seasons, is one challenge to which the SLAM technology is linked.The algorithms used in these environments also take a great deal of time.
They are inefficient, so they are only used in limited environments, which can impede the market’s expansion.
In this report, the global SLAM market has been segmented based on type, technology, application and geography.Based on type, the SLAM market has been categorized into two-dimensional (2D) SLAM and three-dimensional (3D) SLAM.
The 2D segment is dominating the market, with REDACTED% of the market share, due to its increased usage in industrial and residential robots applications.Based on technology, the market has been segmented into EKF SLAM, graph based SLAM, fast SLAM and others.
EKF based SLAM accounted for the dominant share, with REDACTED% in the market, attributed to its increased use over other algorithms, as it exhibits consistent behavior in terms of state variables. It also has limited
algorithm complexity over other technologies.
The SLAM market has been regionally segmented into North America, Europe, Asia-Pacific (APAC) and RoW.The North America region is currently the most dominant segment of the global SLAM market.
The APAC region is projected to witness significant growth during the forecast period, primary driven by the increased demand from China and India, which are witnessing rapid economic growth, as well as the expansion of manufacturing facilities.