SLAM（Simultaneous Localization and Mapping）市場：マッピングタイプ、製品、用途、エンドユーザー、地域別、2024年～2031年

SLAM（Simultaneous Localization and Mapping）市場評価、2024年～2031年

同時ローカライゼーションとマッピングは、デバイスやロボットがリアルタイムで環境を理解しマッピングすると同時に、その環境内での自身の位置を決定することを可能にする技術です。これにより、軍事・防衛、製造、その他多様な分野での応用が非常に効率的になります。Verified Market Researchのアナリストによると、世界の同時ローカライゼーションとマッピング市場は、2023年に2億6,200万米ドルの評価を得ています。2031年には18億米ドルの収益と予測されています。

市場の拡大は、AR/VRアプリケーションの需要増加、自律走行車の採用増加、センサー技術の進歩など、数多くの要因に起因しています。このようなSLAMアプリケーションの急増により、市場は2024年から2031年にかけてCAGR 41.6％で成長します。

SLAM（Simultaneous Localization and Mapping）市場：定義/概要

ローカライゼーションとマッピングの同時進行は、環境をナビゲートする無人車両やロボットの助けを借りて地図を作成するプロセスです。SLAMは、ロボット地図作成またはロボットマッピングで使用されるシステムです。この手順では、複雑な計算、アルゴリズム、感覚入力を用いてナビゲーションを行う。これにより、人間が地図を作成するのが危険な環境でも、地理情報システム（GIS）データを遠隔地から作成することができます。地図の開発やアップグレードの際に遭遇する計算上の困難は、ローカライゼーションとマッピングの同時進行と呼ばれます。

SLAMアプリケーションを目的として設計されたロボットは、SLAMロボットと呼ばれています。SLAM（Simultaneous Localization and Mapping）は、ロボットや無人車両が地図を生成すると同時に、生成した地図を利用して環境をナビゲートするために採用される技術です。ビジュアルSLAMシステムはリアルタイムで動作する必要があるため、定期的に位置情報とマッピングデータを別々にバンドル調整する必要があるが、最終的に統合するまでの処理速度を高速化するために同時に行う。SLAM技術は、拡張現実、仮想画像の投影、多様なフィールドロボットなど、数多くの用途があります。ローカライゼーションとマッピングの同時処理技術により、精度は大幅に向上しました。

世界のSLAM（Simultaneous Localization and Mapping）市場を促進する要因は？

世界のSLAM市場は、その採用と成長を促進するいくつかの重要な要因によって牽引されています。重要な要因の1つは、多様な産業で自律移動ロボットや車両の需要が高まっていることです。これらのロボットや車両は、人間の介入なしに周囲の環境を正確にナビゲートしマッピングするSLAM技術に依存しています。

製造、物流、農業などの産業で自動化が進むにつれて、堅牢なSLAMソリューションの需要は増加の一途をたどっています。拡張現実（AR）や仮想現実（VR）アプリケーションの人気が高まっています。SLAM技術は、ユーザーの位置と周囲の環境をリアルタイムで正確に追跡することで、没入感のあるAR体験を可能にする上で重要な役割を担っています。

バーチャルリアリティアプリケーションでは、SLAMは物理的な空間をマッピングし、デジタルコンテンツをシームレスに統合することで、本物のバーチャル環境の作成を容易にします。ゲーム、エンターテインメント、教育、企業アプリケーションにおけるARとVRの使用事例の増加が、高度なSLAMソリューションの需要を促進しています。

さらに、特にLIDAR、カメラシステム、慣性センサーの分野におけるセンサー技術の進歩により、SLAMアルゴリズムの精度と信頼性が大幅に向上しています。このような技術進歩により、多様な環境や課題下で動作可能な、より堅牢で効率的なSLAMシステムの開発が進んでいます。その結果、ロボット産業、自動車産業、家電産業など、さまざまな産業でSLAM技術を製品やサービスに取り入れ、性能や機能性を向上させるという課題が増加しています。

SLAMの売上を急落させる課題とは？

有望な機会があるにもかかわらず、世界のSLAM市場は、その普及と成長を妨げる可能性のあるいくつかの課題に直面しています。SLAMアルゴリズムの複雑さと計算の厳密さ、特にリアルタイム・アプリケーションの場合。計算資源を効率的に管理しながら、リアルタイムで環境を正確にマッピングし、位置を追跡できるロバストなSLAMシステムの開発は、依然として技術的な障害となっています。

さらに、屋外や散らかった屋内空間など、多様で動的な環境において高い精度と信頼性を達成することも課題となっています。SLAMシステムと既存のハードウェアおよびソフトウェア・プラットフォームとの統合と相互運用性。ロボット工学、自動車、AR（拡張現実）など数多くの産業が、多様なハードウェアコンポーネントやソフトウェアフレームワークに依存しています。SLAMソリューションとこれらの既存プラットフォームとのシームレスな統合と互換性を確保するのは困難で、大規模なカスタマイズと開発努力が必要になることがあります。さらに、多様なSLAMシステムや標準間の相互運用性の懸念は、コラボレーションの障害となり、多様な業界にわたるSLAMベースのアプリケーションのスケーラビリティを妨げる可能性があります。

SLAM技術に関連するプライバシーとセキュリティの懸念は、特に機密データや環境に関わるアプリケーションに課題をもたらします。SLAMシステムは、カメラやLIDARなどのセンサーに依存して物理空間に関するデータを収集・処理するため、潜在的なプライバシー侵害や機密情報への不正アクセスに関する懸念があります。これらの懸念に対処し、データのプライバシーと完全性を保護する強固なセキュリティ対策を採用することは、SLAM技術の信頼と採用を促進するために不可欠です。

目次

第1章 SLAM（Simultaneous Localization and Mapping）の世界市場：イントロダクション

• 市場概要
• 調査範囲
• 前提条件

第2章 エグゼクティブサマリー

第3章 VERIFIED MARKET RESEARCHの調査手法

• データマイニング
• バリデーション
• 一次資料
• データソース一覧

第4章 世界のSLAM（Simultaneous Localization and Mapping）市場展望

• 概要
• 市場力学
  • 促進要因
  • 抑制要因
  • 機会
• ポーターのファイブフォースモデル
• バリューチェーン分析

第5章 SLAM（Simultaneous Localization and Mapping）の世界市場：製品別

• 概要
• スパース法と高密度法
• 直接法と間接法

第6章 SLAM（Simultaneous Localization and Mapping）の世界市場：用途別

• 概要
• モバイルロボット
• スマートAR
• その他

第7章 SLAM（Simultaneous Localization and Mapping）の世界市場：地域別

• 概要
• 北米
  • 米国
  • カナダ
  • メキシコ
• 欧州
  • ドイツ
  • 英国
  • フランス
  • その他欧州
• アジア太平洋
  • 中国
  • 日本
  • インド
  • その他アジア太平洋地域
• 世界のその他の地域
  • ラテンアメリカ
  • 中東・アフリカ

第8章 SLAM（Simultaneous Localization and Mapping）の世界市場：競合情勢

• 概要
• 各社の市場ランキング
• 主な開発戦略

第9章 企業プロファイル

• Google
• Microsoft
• Uber
• Sony
• Clearpath Robotics
• Vecna
• Locus Robotics
• Fetch Robotics
• IRobot
• LG Electronics

第10章 主な発展

• 製品上市／開発
• 合併と買収
• 事業拡大
• パートナーシップと提携

第11章 付録

• 関連調査

Simultaneous Localization and Mapping (SLAM) Market Valuation - 2024-2031

Simultaneous Localization and Mapping is a technology that enables devices or robots to understand and map their environment in real-time while simultaneously determining their own position within that environment. Thereby, rendering highly efficient for further application in the military and defense, manufacturing, and other diverse sectors. According to the analyst from Verified Market Research, the Global Simultaneous Localization and Mapping Market has valuation of USD 262 Million in 2023. The forecast by subjugating the revenue of USD 1.8 Billion in 2031.

The market proliferation predominantly ascribes to numerous factors, such as the rising demand for AR/VR applications, the increasing adoption of autonomous vehicles, and advancements in sensor technologies. This upsurge in the application of SLAM enables the market to grow at aCAGR of 41.6% from 2024 to 2031.

Simultaneous Localization and Mapping (SLAM) Market: Definition/ Overview

Simultaneous localization and mapping is the process of creating a map with the help of an unmanned vehicle or a robot that navigates the environment. Simultaneous localization and mapping is a system used in robot cartography or robot mapping. This procedure employs a complex array of computations, algorithms, and sensory inputs to navigate. It allows for the remote creation of geographic information system (GIS) data in situations where the surroundings are dangerous for humans to map. A computational difficulty encountered during map development or upgrade is referred to as simultaneous localization and mapping.

Robots that have been designed to serve the purpose of SLAM applications are referred to as SLAM robots. Simultaneous localization and mapping (SLAM) is a technique employed by robots or unmanned vehicles to generate a map while simultaneously navigating the environment, utilizing the map it generates. Visual SLAM systems need to operate in real-time, so regularly location and mapping data suffer bundle adjustment separately, but simultaneously to facilitate faster processing speeds before they're ultimately merged. The SLAM technology has numerous applications, including augmented reality, projecting virtual images, and a diverse range of field robots. The accuracy has greatly improved with the help of simultaneous localization and mapping technology.

What's inside a VMR industry report?

Our reports include actionable data and forward-looking analysis that help you craft pitches, create business plans, build presentations and write proposals.

Which are the Drivers Encouraging the Global Simultaneous Localization and Mapping (SLAM) Market?

The Global SLAM market is being driven by several key factors that are driving its adoption and growth. One significant factor is the escalating demand for autonomous mobile robots and vehicles across diverse industries. These robotics and vehicles rely on SLAM technology to navigate and map their surroundings accurately without human intervention.

As industries such as manufacturing, logistics, and agriculture continue to automate their operations, the demand for robust SLAM solutions continues to grow. The escalating popularity of augmented reality (AR) and virtual reality (VR) applications. SLAM technology has a crucial role in enabling immersive AR experiences by accurately tracking the user's position and surroundings in real time.

In virtual reality applications, SLAM facilitates the creation of authentic virtual environments by mapping physical spaces and seamlessly integrating digital content. The increasing use cases for AR and VR in gaming, entertainment, education, and enterprise applications are driving demand for advanced SLAM solutions.

Furthermore, advances in sensor technology, particularly in the fields of LIDAR, camera systems, and inertial sensors, have greatly improved the accuracy and reliability of SLAM algorithms. These technological advances have led to the development of more robust and efficient SLAM systems that are capable of operating in diverse environments and under challenging conditions. Consequently, various industries, such as robotics, automotive, and consumer electronics, challenges are increasingly incorporating SLAM technology into their products and services to enhance their performance and functionality.

What are the Challenges Plummeting the Sales of Simultaneous Localization and Mapping?

Despite the promising opportunities, the global SLAM market faces several challenges that could hinder its widespread adoption and growth. The complexity and computational rigor of SLAM algorithms, particularly in the context of real-time applications. The development of robust SLAM systems that are capable of precisely mapping environments and tracking positions in real time while efficiently managing computational resources, remains a technical obstacle.

Furthermore, it is challenging to achieve high accuracy and reliability in diverse and dynamic environments, such as outdoor settings or cluttered indoor spaces. The integration and interoperability of SLAM systems with existing hardware and software platforms. Numerous industries, including robotics, automotive, and augmented reality, rely on a diverse array of hardware components and software frameworks. It can be difficult and require extensive customization and development efforts to ensure seamless integration and compatibility between SLAM solutions and these existing platforms. Furthermore, interoperability concerns among diverse SLAM systems and standards may pose obstacles to collaboration and hinder the scalability of SLAM-based applications across diverse industries.

Privacy and security concerns associated with SLAM technology pose challenges, especially in applications involving sensitive data or environments. Since SLAM systems rely on sensors such as cameras and LIDAR to collect and process data about physical spaces, there are concerns about potential privacy breaches and unauthorized access to sensitive information. Addressing these concerns and adopting robust security measures to protect data privacy and integrity are essential for fostering trust and adoption of SLAM technology.

Category-Wise Acumens

Will Increase in the Production of UAVs Boost the Growth of the Market?

According to VMR analysis, the escalating utilization of unmanned Aerial Vehicles (UAVs), commonly referred to as drones, is presently poised to significantly impact the expansion of enterprises operating in diverse industries. UAVs provide numerous advantages across various industries, including enhanced operational efficacy, cost reduction, enhanced safety, and access to remote or hazardous environments. In various industries, such as agriculture, construction, infrastructure inspection, aerial photography, and emergency response, unmanned aerial vehicles (UAVs) provide companies with the opportunity to acquire valuable data, monitor assets, and execute tasks with greater speed, precision, and flexibility.

In agriculture, UAVs equipped with specialized sensors can monitor crop health, assess soil conditions, and optimize irrigation and pesticide application, leading to higher yields and reduced resource usage. In construction and infrastructure, UAVs can perform aerial surveys, monitor construction progress, and inspect structures, improving project planning, monitoring, and maintenance processes while reducing costs and risks associated with manual inspections. In industries such as oil and gas, utilities, and public safety, UAVs can conduct aerial surveillance, monitor pipelines and power lines, and assist in search and rescue operations, enhancing operational efficiency and safety. This surging application of UAVs is bolstering demand for SLAM over the forecast period.

How will Sales of Deep Learning Based SLAM Fare for SLAM Market?

Deep Learning Based Simultaneous Localization and Mapping (SLAM) is experiencing significant growth. Deep learning techniques have revolutionized the field of computer vision, enabling more accurate and robust perception capabilities. Deep learning models can extract meaningful features from sensor data, such as images and point clouds, by leveraging neural networks and large datasets. This allows for more precise localization and mapping in complex environments.

The increasing availability of powerful hardware, such as graphics processing units (GPUs) and specialized accelerators like tensor processing units (TPUs), has facilitated the training and deployment of deep learning models for SLAM applications. These hardware advances enable faster processing of large volumes of sensor data, making real-time SLAM feasible even on resource-constrained devices.

The proliferation of data-driven approaches and open-source frameworks has lowered the barrier to entry for developers and researchers interested in implementing SLAM solutions. The democratization of technology has sparked innovation and collaboration within the SLAM community, resulting in rapid advancements in algorithmic performance and scalability.

Global Simultaneous Localization and Mapping Report Methodology

Country/Region-wise Acumens

Which Region has the Most Potential for Growth in Simultaneous Localization and Mapping?

The Asia-Pacific region presents significant potential for the advancement of Simultaneous Localization and Mapping (SLAM) technology. With the rapid expansion of economies, the escalating urbanization, and the escalating investments in robotics, autonomous vehicles, and augmented reality applications, there is a rising demand for precise and dependable localization and mapping solutions across diverse industries.

Countries such as China, Japan, and South Korea are at the forefront of technological innovation, with thriving ecosystems of research institutions, start-ups, and established companies driving advancements in SLAM algorithms and applications.

Moreover, the extensive manufacturing base and consumer market in the region present ample prospects for the deployment of SLAM-enabled products and services, rendering Asia-Pacific a crucial growth market for SLAM technology.

Which Region is Dominating in Simultaneous Localization and Mapping Market?

North America is emerging as a dominant force within the Simultaneous Localization and Mapping (SLAM) market. This prominence is attributed to several factors. North America has a strong ecosystem of technology companies, research institutions, and start-ups that specialize in robotics, autonomous vehicles, augmented reality, and other SLAM-enabled applications.

Silicon Valley, California, and the Boston area, Massachusetts, are major hubs for innovation and investment in SLAM technology. Furthermore, North America is home to leading players in the automotive industry, who are investing heavily in autonomous driving technology and leveraging SLAM for localization and mapping capabilities.

Favorable government initiatives, supportive regulatory frameworks, and high consumer acceptance of emerging technologies further contribute to North America's dominance in the SLAM market. In general, the region continues to hold a significant position in the research, development, and commercialization of SLAM solutions, rendering it a pivotal player in the global market landscape.

Competitive Landscape

The competitive landscape in global simultaneous localization and mapping markets is dynamic and evolving, driven by changing customer preferences, technological advancements, and market dynamics. Providers continue to innovate and differentiate their offerings to stay competitive and capture market share in this rapidly growing industry.

Some of the prominent players operating in the global simultaneous localization and mapping Market include:

Alphabet

Amazon Robotics

Apple

Microsoft

Clearpath Robotics

Aethon

The Hi-Tech Robotic Systemz

Facebook

Intellias

MAXST

Intel

Magic Leap

Rethink Robotics

Skydio

NavVis

Mobile Industrial Robot Aps

Google

Uber

Sony

Vecna

Locus Robotics

Fetch Robotics

IRobot

LG Electronics

Wikitude

SLAM

DJI

AVIC

Latest Developments:

In October 2020, Apple Inc. acquired Vilynx Inc. Apple's artificial intelligence solutions, which are merged with the iPhone and its applications, strengthened as an outcome of this acquisition.

In February 2020, Facebook, Inc., acquired Scape Technologies Ltd. The acquisition provides Facebook with such a huge number of SLAM-based augmented reality possibilities.

In December 2018, Intel (US) partnered with Waymo (US), an Alphabet subsidiary capable of providing computational power for Level 4 and 5 autonomous vehicles.

In June 2020, OTTO Motors, a Clearpath Robotics division, raised USD 29 million in Series C funding to support the continued growth of its autonomous mobile robot (AMR) platform. This funding was used to increase OTTO's global network of delivery partners and boost its product roadmap for corporate clients, with a focus on the company's industry-leading automation technology.

In May 2020, Kudan Inc has developed KudanSLAM1 in ToF cameras utilizing Analog Devices, K.K. products, as well as the collaborative development of 3D SLAM demonstration software running on ROS. The use of ToF cameras in independent robotics enables 3D SLAM to function even in dimly lit environments where standalone RGB cameras are ineffective.

TABLE OF CONTENTS

1. INTRODUCTION OF GLOBAL SIMULTANEOUS LOCALIZATION AND MAPPING (SLAM) MARKET

• 1.1. Overview of the Market
• 1.2. Scope of Report
• 1.3. Assumptions

2. EXECUTIVE SUMMARY

3. RESEARCH METHODOLOGY OF VERIFIED MARKET RESEARCH

• 3.1. Data Mining
• 3.2. Validation
• 3.3. Primary Interviews
• 3.4. List of Data Sources

4. GLOBAL SIMULTANEOUS LOCALIZATION AND MAPPING (SLAM) MARKET OUTLOOK

• 4.1. Overview
• 4.2. Market Dynamics
  • 4.2.1. Drivers
  • 4.2.2. Restraints
  • 4.2.3. Opportunities
• 4.3. Porters Five Force Model
• 4.4. Value Chain Analysis

5. GLOBAL SIMULTANEOUS LOCALIZATION AND MAPPING (SLAM) MARKET, BY PRODUCT

• 5.1. Overview
• 5.2. Sparse and Dense Methods
• 5.3. Direct and Indirect Methods

6. GLOBAL SIMULTANEOUS LOCALIZATION AND MAPPING (SLAM) MARKET, BY APPLICATION

• 6.1. Overview
• 6.2. Mobile Robots
• 6.3. Smart AR
• 6.4. Other

7. GLOBAL SIMULTANEOUS LOCALIZATION AND MAPPING (SLAM) MARKET, BY GEOGRAPHY

• 7.1 Overview
• 7.2 North America
  • 7.2.1 U.S.
  • 7.2.2 Canada
  • 7.2.3 Mexico
• 7.3 Europe
  • 7.3.1 Germany
  • 7.3.2 U.K.
  • 7.3.3 France
  • 7.3.4 Rest of Europe
• 7.4 Asia Pacific
  • 7.4.1 China
  • 7.4.2 Japan
  • 7.4.3 India
  • 7.4.4 Rest of Asia Pacific
• 7.5 Rest of the World
  • 7.5.1 Latin America
  • 7.5.2 Middle East and Africa

8. GLOBAL SIMULTANEOUS LOCALIZATION AND MAPPING (SLAM) MARKET COMPETITIVE LANDSCAPE

• 8.1. Overview
• 8.2. Company Market Ranking
• 8.3. Key Development Strategies

9. COMPANY PROFILES

• 9.1. Google
  • 9.1.1 Overview
  • 9.1.2 Financial Performance
  • 9.1.3 Product Outlook
  • 9.1.4 Key Developments
• 9.2. Microsoft
  • 9.2.1. Overview
  • 9.2.2. Financial Performance
  • 9.2.3. Product Outlook
  • 9.2.4. Key Developments
• 9.3. Uber
  • 9.3.1. Overview
  • 9.3.2. Financial Performance
  • 9.3.3. Product Outlook
  • 9.3.4. Key Developments
• 9.4. Sony
  • 9.4.1. Overview
  • 9.4.2. Financial Performance
  • 9.4.3. Product Outlook
  • 9.4.4. Key Developments
• 9.5. Clearpath Robotics
  • 9.5.1. Overview
  • 9.5.2. Financial Performance
  • 9.5.3. Product Outlook
  • 9.5.4. Key Developments
• 9.6. Vecna
  • 9.6.1. Overview
  • 9.6.2. Financial Performance
  • 9.6.3. Product Outlook
  • 9.6.4. Key Developments
• 9.7. Locus Robotics
  • 9.7.1. Overview
  • 9.7.2. Financial Performance
  • 9.7.3. Product Outlook
  • 9.7.4. Key Developments
• 9.8. Fetch Robotics
  • 9.8.1. Overview
  • 9.8.2. Financial Performance
  • 9.8.3. Product Outlook
  • 9.8.4. Key Developments
• 9.9. IRobot
  • 9.9.1. Overview
  • 9.9.2. Financial Performance
  • 9.9.3. Product Outlook
  • 9.9.4. Key Developments
• 9.10. LG Electronics
  • 9.10.1. Overview
  • 9.10.2. Financial Performance
  • 9.10.3. Product Outlook
  • 9.10.4. Key Developments

10 KEY DEVELOPMENTS

• 10.1 Product Launches/Developments
• 10.2 Mergers and Acquisitions
• 10.3 Business Expansions
• 10.4 Partnerships and Collaborations

11 Appendix

• 11.1 Related Research