モバイルロボット_物流、倉庫、搬送用途 2022-2042年: IDTechEx

物流における全モバイルロボットの市場売上は2042年までに3000億ドルを超える規模に。

モバイルロボット_物流、倉庫、搬送用途 2022-2042年

AGV、グリッドベースAGC、AMR、モバイルケースピッキングロボット、モバイルマニピュレーター、重作業用自動運転レベル4トラック、自動運転ラストワンマイル配送用バン、ロボット、ドローン、技術、市場および見通し。


製品情報 概要 目次 価格 Related Content
モバイル(移動式)ロボットは物流業界の多くの課題に対する優れたソリューションとなりえます。このレポートでは有力企業、技術および市場、20年先の市場見通しおよび物流における14種の豊富なモバイル(移動式)ロボット製品例を紹介します。読者は現在の市場状況、技術の利用のされ方、技術トレンド、将来の市場の見通しに関して深い理解を得ることができます。
「モバイルロボット_物流、倉庫、搬送用途 2022-2042年」が対象とする主なコンテンツ
(詳細は目次のページでご確認ください)
• 全体概要
• 物流におけるモバイルロボット技術: 概要およびイントロダクション
  • モバイルロボット: イントロダクション
  • 物流におけるモバイルロボットの活用
  • 現在の市場における主要な影響要因
  • 市場の資金調達と買収トレンド
  • 予測の算定方式
• 資材運搬用モバイルロボット
  • 製品紹介
  • 技術比較
  • 市場展望および有力企業分析
  • 各種見通し
  • 製品と用途例
• モバイルピッキング・ロボット
  • 製品紹介
  • 市場展望分析
  • 各種見通し
  • 製品と用途例
• 重作業用自動運転レベル4トラック
  • 長距離トラック輸送のペインポイント
  • 市場展望分析
  • 各種見通し
  • 製品と用途例
• 自動運転ラストワンマイル配送
  • イントロダクション
  • 関係する技術
  • 規制に関する最新情報
  • 市場の歴史および展望分析
  • 各種見通し
  • 製品と用途例
  • 見通しのサマリー
• 全体サマリー
• 製品カテゴリー別見通し
 
「モバイルロボット_物流、倉庫、搬送用途 2022-2042年」は以下の情報を提供します
技術、市場のペインポイントおよび規制 - 分析、比較、トレンド
  • 物流モバイルロボットの全体像
  • 採用されている技術詳細および比較
  • 詳細な製品形態比較および拡大動向
  • 技術と製品の進化の予測
  • 現在の物流におけるモバイルロボットの技術的限界
  • 物流業界の現在の主なペインポイント
  • モバイルロボットがペインポイントにどう対処するのか
  • 自動運転トラック輸送とラストワンマイル配送の規制に関する最新情報
  • 自動運転配送の規制動向
  • 資金調達動向
市場見通しおよび分析:
  • 物流網全体を網羅するモバイルロボット14種の製品別20年先の市場見通し
  • 現在の市場展望、影響要因および主要有力企業に関する分析
  • 既存の市場および新しい市場の双方に対する製品例と応用事例の調査
 
Mobile robots can be an excellent solution to many issues in the logistics industry. This report provides a comprehensive analysis of major players, technologies, and markets, 20-year market forecasts, and abundant product examples of 14 different forms of mobile robots in logistics. It will help readers have a deeper understanding of the current market landscape, how the technologies are used, the technology trend, and the future market outlook.
Automation in the warehousing and logistics chain is a growing market. A particularly exciting subset of this is the use of mobile robots, autonomous vehicles, and drones for automation of movement-based tasks. This field encompasses all manner of mobile robotic devices used in logistics, such as robotic carts/vehicles, on-road autonomous trucks, and drones, which help goods in their journey from origin to destination. This report finds that the market for mobile robots (including trucks and drones) in logistics, delivery and warehousing is likely to reach a staggering $83 and $334 Billion in 2032 and 2042, respectively.
 
This report provides a comprehensive analysis of major players, technologies, and markets. It covers relatively mature and emerging logistics mobile robotic products including different forms of automated guided vehicles (AGVs), autonomous mobile robots (AMRs), grid-based automated guided carts (grid-based carts), case-picking robots, mobile manipulators, heavy-duty level-4 autonomous trucks, last mile autonomous delivery vans, robots and drones.
 
This report provides technology roadmaps and twenty-year market forecasts in market revenue, for all the technologies outlined above (14 forecast lines). The forecasts are built as a twenty-year model because IDTechEx's technology roadmap suggests that these changes will take place over long timescales. In IDTechEx's detailed forecasts the different stages of market growth are clearly explained, and the key assumptions/conditions as well as data points that underpin the model are outlined.
 
Furthermore, the report has detailed analysis about key technologies used in mobile robotics (e.g., navigation), typically used sensors and predictions of technological trend. In addition, it includes the most recent regulatory changes on autonomous driving related products (e.g., autonomous trucks, autonomous delivery vans, etc.) and anticipates the key timepoints and trends for deregulations. Our technology assessments and regulation predictions feed directly into our market forecast model, governing the adoption timescales and the estimated technology market share evolutions.
 
IDTechEx further provides investment/trend analysis, always seeking to put each technology within its greater quantitative as well as qualitative context. Also included are company interviews/profiles/updates. Company profiles and interviews provide valuable insight on company positioning, strategy, opportunities, and challenges, more than 25 of which can also be found on our subscription portal for more details, as IDTechEx has either interviewed or carried out deep research with these companies.
 
Intralogistics mobile robots
For a long time, automated guide carts and vehicles (AGC and AGV) have been in use. They are infrastructure dependent, their installation is time-consuming, and their workflow is difficult to adapt. Consequently, as a technology, they are on relatively shaky ground, because the technology is evolving towards more autonomous and infrastructure-independent navigation. But they are more reliable in terms of transporting heavy loads for a long distance. Therefore, we forecast their market will have a healthy growth in the following years but start to decrease between 2032-2037 (depending on product forms). They will increasingly become confined to ever narrower market niches.
 
One very bright spot for automated robots is in goods-to-person grid-based automated carts (grid-based AGCs) for fulfilment centres and large warehouses. Special robot-only zones are created within warehouses in which these robot fleets move racks at high speeds to a manned picking station, leading to clear and proven productivity gains. This will be a fast-growing market space by 2030.
 
The navigation technology is transitioning from automated to autonomous, enabled by better SLAM algorithms. With no additional requirements on building infrastructure or changing the environment, autonomous mobile robots (AMRs) can save more cost and time, being easier to scale the fleet and to be adopted flexibly. We assess that the market for such will continuously grow by 2042. There have also been more prominent investments and acquisitions on this technology in recent years.
Mobile picking robots
Picking technology is an essential component of logistics automation. Today, many companies focus on multi-layer case picking robots that pick and handle multiple regularly shaped boxes or totes with their telescopic forks or vacuum grippers for "carton-to-person" working mode. The similarities and differences between this mode and "shelf-to-person" one of grid-based AGCs have been thoroughly discussed in the report. There are also a few companies having integrated robotic manipulators on mobile platforms for picking irregularly shaped complex items, but the picking performance is very limited yet. We forecast case-picking robots will dominate the market for a long time and the market growth speed for mobile manipulators will only accelerate after 2035.
 
Heavy-duty level-4 trucking
The major pain points nowadays in the trucking industry, and especially long-haul trucking, include high operation cost, driver management and safety. Implementing high-level autonomous heavy-duty trucks can well address those pain points, and potentially can improve the safety during driving. According to known recent regulatory changes and information about level-4 autonomous truck pre-orders, IDTechEx anticipate the market revenue will start to be largely generated in 2025.
 
Autonomous last mile delivery robotic products
Autonomous last mile delivery is also an emerging market. There are mainly three forms of products - autonomous delivery vans, sidewalk robots and autonomous delivery drones. Last mile delivery is the most expensive part of delivering a parcel. Autonomous last mile delivery solutions, however, can hugely save the cost and improve the delivery efficiency in a more ecological way. It is estimated that implementing autonomous last mile delivery solutions can potentially save 55% of current costs in the short-term, and may save over 80% in the long-term future.
 
Autonomous delivery vans and sidewalk robots are both ground-based delivery solutions. Most of them are electrically powered and drive at a relatively slow speed in limited known neighbourhood areas, which ease the technological burden of perceiving in a long range and constructing maps in real time. Compared to sidewalk robots, the vans have large room and longer battery life, able to deliver to multiple locations with more and heavier items; while sidewalk robots can be more easily formed to a larger fleet size and deliver to various customers simultaneously because the robot has a lower unit cost. Drone delivery, as a faster autonomous delivery option, now however faces more obstacles on technologies, regulations and infrastructure support. Based on our analysis and forecast, the autonomous delivery vans will be the mainstream product in last mile delivery, accounting for over 75% of ground-based solutions in 2042; on the other hand, drone delivery will have a smaller market and a later market take-off point.
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詳細
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アイディーテックエックス株式会社 (IDTechEx日本法人)
担当: 村越美和子 m.murakoshi@idtechex.com
Table of Contents
1.EXECUTIVE SUMMARY
1.1.Executive introduction
1.1.1.How can mobile robots be used in logistics?
1.1.2.Major impact factors for the current market of logistics mobile robots
1.1.3.Major impact factors for the current market of logistics mobile robots
1.1.4.Sales leap in 2022
1.1.5.Forecast summary - mobile robots excluding L4 trucks
1.1.6.Forecast summary - heavy-duty L4 trucks
1.1.7.Forecast numbers - intralogistics transporting robots
1.1.8.Forecast numbers - other products and the sum of market revenue
1.2.Chapter-by-chapter findings, analysis and conclusions
1.3.Intralogistics material transporting
1.3.1.Different types of mobile robotics in material handling
1.3.2.Different types of mobile robots in intralogistics material transporting
1.3.3.Mobile robots vs. fixed automation
1.3.4.Market outlook for intralogistics material transporting robots
1.4.Mobile picking
1.4.1.Two forms of mobile picking robots on the current market
1.4.2.Market outlook for mobile picking robots
1.5.Level-4 autonomous trucking
1.5.1.Market outlook for heavy-duty level-4 autonomous trucks
1.6.Last-mile delivery
1.6.1.Why autonomous last mile delivery?
1.6.2.Market outlook for last mile delivery robots and drones
2.MOBILE ROBOTICS IN LOGISTICS: OVERVIEW AND INTRODUCTION
2.1.What are mobile robots?
2.2.Why mobile robots?
2.3.How can mobile robots be used in logistics?
2.4.SLAM
2.5.Typical sensors for object detection
2.6.Major impact factors for the current market of logistics mobile robots
2.7.Labour shortage
2.8.E-commerce
2.9.Chip shortage
2.10.COVID impact
2.11.Sales leap in 2022
2.12.Robot-as-a-Service (RaaS)
2.13.Funding trending
2.14.Acquisition
2.15.Methodology and assumptions for forecasts
2.16.Illustration of S-curve
3.INTRALOGISTICS MATERIAL TRANSPORTING MOBILE ROBOTS
3.1.1.Different types of mobile robotics in material handling
3.1.2.Different types of mobile robots in intralogistics material transporting
3.1.3.Automated Guide Vehicles & Carts (AGV/Cs)
3.1.4.Grid-based automated guided carts (grid-based AGC)
3.1.5.Autonomous Mobile Robots(AMRs)
3.2.Comparison of technologies
3.2.1.Transition to AGVs and AMRs
3.2.2.Mobile robots vs. fixed automation
3.2.3.Why use mobile robots in warehouses?
3.2.4.AGV/Cs vs. AMRs
3.2.5.Technology evolution towards fully autonomous independent mobile robots
3.3.Players
3.3.1.Players - Region
3.3.2.Players - Funding
3.3.3.Players - Leading Companies for AGVs
3.3.4.AGV companies: partnership with forklift companies
3.3.5.Players - Leading Companies for grid-based AGC
3.3.6.Players - Leading Companies for AMR
3.4.Forecasts
3.4.1.Forecast - market size by product types
3.4.2.Forecast - Forklift and tow tractor AGVs
3.4.3.Forecast - Unit load and other AGVs
3.4.4.Forecast - Grid-based AGC
3.4.5.Forecast - Grid-based AGC
3.4.6.Other forms of goods-to-person robot
3.4.7.Forecast - Unit load AMR, Heavy-load AMV, other material transporting AMR
3.4.8.Toc for examples
3.5.Examples of AGVs
3.5.1.Toyota Material Handling
3.5.2.Dematic
3.5.3.ASTI: acquired by ABB in July 2021
3.5.4.Linde
3.5.5.Daifuku
3.5.6.SSI Scheafer
3.5.7.Murata Machinery
3.5.8.Swisslog
3.5.9.Multiway
3.5.10.America in Motion
3.6.Examples of grid-based AGCs
3.6.1.Amazon Robotics (formerly Kiva)
3.6.2.Amazon Robotics (formerly Kiva)
3.6.3.Geek+
3.6.4.Hikrobot
3.6.5.GreyOrange
3.6.6.Swisslog
3.6.7.Quicktron
3.6.8.Prime Robotics
3.6.9.Malu Innovation
3.6.10.Scallog
3.7.Examples of AMRs
3.7.1.Omron
3.7.2.SeeGrid
3.7.3.Mobile Industrial Robots (MiR)
3.7.4.Locus Robotics
3.7.5.Fetch Robotics
3.7.6.ForwardX Robotics
3.7.7.Standard Robots
3.7.8.Milvus Robotics
3.7.9.6 River Systems
3.7.10.Honeywell Intelligrated
3.7.11.KNAPP
3.7.12.Otto Motors
3.7.13.Syrius Robotics
4.MOBILE PICKING ROBOTS
4.1.1.Two forms of mobile picking robots on the current market
4.1.2.Case-picking robots
4.1.3.Comparison: grid-based AGCs and multi-layer case-picking robots
4.1.4.Navigation technologies of case-picking robots
4.1.5.Mobile manipulators
4.1.6.Manipulator picking algorithm evolution
4.2.Players
4.2.1.Players - case-picking mobile robots
4.2.2.Players - mobile picking manipulators
4.2.3.Hybrid mobile manipulator
4.3.Forecasts
4.3.1.Forecasts
4.3.2.Forecasts - case-picking robots
4.3.3.Forecasts - mobile picking manipulators
4.3.4.Toc of examples
4.4.Examples of case-picking robots
4.4.1.HAI Robotics
4.4.2.Geek+
4.4.3.Exotec Systems
4.4.4.InVia Robotics
4.4.5.Magazino
4.4.6.BionicHive
4.4.7.Caja Robotics
4.5.Examples of mobile picking manipulators
4.5.1.IAM Robotics
4.5.2.IAM Robotics
4.5.3.Fetch Robotics
4.5.4.Youibot
5.HEAVY-DUTY LEVEL-4 AUTONOMOUS TRUCKS
5.1.1.Pain points in the trucking industry
5.1.2.Why autonomous trucks?
5.1.3.SAE levels of automation
5.1.4.Level-2 and level-4 trucking
5.1.5.Level-4 MaaS for trucking
5.1.6.Authorities for regulating autonomous driving
5.1.7.The Autonomous Legal Race
5.2.Players
5.2.1.Funding
5.2.2.Players
5.2.3.Market readiness level of L4 autonomous truck companies
5.3.Forecasts
5.3.1.Forecast
5.3.2.ToC of examples
5.4.Examples of level-4 autonomous trucking companies
5.4.1.TuSimple
5.4.2.TuSimple's AFN
5.4.3.TuSimple's unique perception solution
5.4.4.Perception system of TuSimple's autonomous trucks
5.4.5.TuSimple's enhanced night vision camera system
5.4.6.World's first fully autonomous semi-truck operating on public roads without human intervention
5.4.7.Embark
5.4.8.Embark: sensors
5.4.9.Einride
5.4.10.Einride: a closer look into the T-pod and E-truck
5.4.11.Einride: sensors of T-pod
5.4.12.Kodiak Robotics
5.4.13.Plus.ai
5.4.14.FABU
5.4.15.Volvo Truck
5.4.16.Daimler
5.4.17.Waymo Driver in autonomous trucks
5.4.18.Hyundai catching up in the autonomous trucking race
6.AUTONOMOUS LAST MILE DELIVERY
6.1.1.What is last mile delivery?
6.1.2.Last mile delivery: the most expensive part
6.1.3.Why autonomous last mile delivery?
6.1.4.Supporting infrastructures
6.1.5.How warehouse infrastructures goes de-centralized to adapt to e-commerce needs?
6.1.6."Last metre" delivery: robot delivery to doorsteps
6.1.7.How can the items be autonomously delivered in last mile?
6.1.8.Comparison: ground-based vehicles vs. drones
6.1.9.Comparison: ground-based vehicles vs. drones
6.2.Technologies
6.2.1.Technologies for ground-based delivery vehicles: sensors
6.2.2.Technologies for ground-based delivery vehicles: localisation and mapping
6.2.3.Technologies for ground-based delivery vehicles: vehicle connection
6.2.4.Technologies for ground-based delivery vehicles: teleoperation and cyber security
6.2.5.Technologies for ground-based delivery vehicles: restrictions
6.2.6.Technologies for drones: two forms of designs
6.2.7.Technologies for drones: sensors
6.2.8.Technologies for drones: restrictions
6.3.Regulations
6.3.1.Regulations - for delivery vehicles
6.3.2.Regulation recent updates - for delivery vehicles
6.3.3.Regulation - for delivery drones
6.3.4.Regulation recent updates - for delivery drones
6.4.Market players
6.4.1.Players - funding of start-ups
6.4.2.Players - number of companies: share by region
6.4.3.Players - what do they deliver now?
6.4.4.Players - autonomous delivery ground-based vehicles
6.4.5.Players - autonomous delivery drones
6.4.6.Timeline - drone delivery companies
6.5.Forecast
6.5.1.Market revenue forecasts for autonomous last mile delivery vans, sidewalk robots and drones
6.5.2.Cost comparison - employing human delivery drivers vs. ground-based autonomous delivery vans
6.5.3.Forecasts - autonomous delivery ground-based vehicles
6.5.4.Forecasts - autonomous delivery ground-based vehicles
6.5.5.Forecasts - autonomous delivery drones
6.5.6.ToC for examples
6.6.Examples of autonomous last mile delivery vans
6.6.1.Nuro
6.6.2.Neolix
6.6.3.JD.com
6.6.4.Meituan
6.6.5.Alibaba
6.6.6.Cleveron
6.6.7.Udelv
6.6.8.Refraction.ai
6.7.Examples of autonomous last mile delivery sidewalk robots
6.7.1.Starship Technologies
6.7.2.ZMP
6.7.3.Amazon
6.7.4.Kiwibot
6.7.5.Serve Robotics (formerly Postmates X)
6.7.6.Robby Technologies
6.8.Examples of autonomous last mile delivery drones
6.8.1.Amazon Prime Air: when will it be ready?
6.8.2.Zipline
6.8.3.Wing
6.8.4.Matternet
6.8.5.Flytrex
6.8.6.Wingcopter
6.8.7.Flirtey
6.8.8.Antwork
7.FORECAST SUMMARY
7.1.Overall forecasts
7.1.1.Overall forecasts - mobile robots excluding L4 trucks
7.1.2.Overall forecasts - heavy-duty L4 trucks
7.1.3.Forecast numbers - intralogistics transporting robots
7.1.4.Forecast numbers - other products and the sum of market revenue
7.2.Market revenue forecasts by product categories
7.2.1.Forecasts - AGVs
7.2.2.Forecasts - grid-based AGC
7.2.3.Forecasts - AMRs
7.2.4.Forecasts - mobile case-picking robots
7.2.5.Forecasts - mobile manipulators
7.2.6.Forecasts - heavy-duty autonomous L4 trucks
7.2.7.Forecasts - ground-based autonomous last mile delivery vehicles
7.2.8.Forecasts - autonomous last mile delivery drones
 

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レポート概要

スライド 298
フォーキャスト 2042
発行日 Jan 2022
ISBN 9781913899882
 

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