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Sensors for Robotics 2023-2043: Technologies, Markets, and Forecasts

ロボティクス用センサー 2023-2043年：技術、市場、予測

この調査レポートは、は、9種類の一般的なセンサー、9種類のロボット、29種類のアプリケーションを深く掘り下げ、主要な実現技術、プレーヤー、市場を詳細に分析し、今後20年間の市場規模や販売量の傾... もっと見る

出版社	出版年月	価格	ページ数	言語
IDTechEx アイディーテックエックス	2022年12月1日	お問い合わせくださいライセンス・価格情報注文方法はこちら	251	英語

※価格はデータリソースまでお問い合わせください。

Table of Contents

Summary

この調査レポートは、は、9種類の一般的なセンサー、9種類のロボット、29種類のアプリケーションを深く掘り下げ、主要な実現技術、プレーヤー、市場を詳細に分析し、今後20年間の市場規模や販売量の傾向を示すきめ細かい予測を行っています。

主な掲載内容（目次より抜粋）

・機能別・課題別センサー

・ナビゲーションとマッピングのためのセンサー

・衝突検知と安全性のためのセンサー

・ロボットにおけるその他のセンサ

・ロボットのタイプ別センサー

・企業情報

Report Summary

Robots are, in essence, machines with autonomy. To enable their autonomy, a suite of sensors is needed to achieve the requirements of different tasks such as autonomous navigation, object detection, proximity sensing, and many others. Sensors have been widely used in a number of industries, and thanks to the increasing technology readiness, the costs of various sensors have gradually decreased over the past few years, enabling greater adoption within robotics. Robots, as highly integrated machines, contain many sensors ranging from optical encoders, and current sensors, to inertial measurement units, cameras, LiDAR, and many others.

Depending on the data collected, sensors can be segmented into two primary categories: proprioceptive and exteroceptive sensors. Proprioceptive sensors collect internal data such as speed, torque, and position. These sensors are usually used for robotic control. On the contrary, exteroceptive sensors collect external data (surroundings) and sense environmental parameters, such as the distance of an obstacle, external force exerted on the robot, and many other inputs. Tactile sensors, vision sensors (cameras), and proximity sensors (e.g. LiDAR, radar, ultrasonic sensors, stereo cameras, etc) are several typical examples of exteroceptive sensors. Driven by the increasing adoption of robots and the increasing demand for 'intelligent' robots, IDTechEx concludes that sensors for robotics will experience a rapid growth over the upcoming two decades. IDTechEx's latest report 'Sensors for Robotics: Technologies, Markets, and Forecasts 2023-2043' takes a deep dive into nine types of common sensors, nine types of robots, and 29 applications with an in-depth analysis of the key enabling technologies, players, and markets with granular forecasts showing the market size and sales volume trend for the next 20 years. The chart below shows an overview of the robots, sensors, and tasks covered in the report.

Overview of key sensors, robot types, and task themes covered in this report.

Source: IDTechEx

Sensors for navigation and mapping

Autonomous mobility has gained significant momentum over the past decade thanks to the development of autonomous driving technologies. As one of the most important factors for robot autonomy, autonomous mobility enables robots to move independently with minimum human supervision and fulfill many tasks such as logistics, delivery, weeding and seeding, mapping, and exploration. Autonomous mobility consists of two steps: mapping and navigation. A robot initially needs to map the environment to construct a model made of point clouds and plan a moving trajectory/path, then follow the proposed trajectory and use navigation sensors for localizing. Both steps require sensors for object detection, navigation, and collecting data from the ambient environment. In practice, depending on the working environments, different navigation and mapping sensors are often used together, and sensor fusion algorithms are implemented to process data from different sensors (sensory modalities). Typical navigation and mapping sensors include LiDAR, radar, cameras, GPS/GNSS, and ultrasonic sensors (1D and 3D). The table below compares the advantages and disadvantages of some of these sensors, a more in-depth technology analysis can be found in IDTechEx's report - 'Sensors for Robotics: Technologies, Markets, and Forecasts 2023-2043'.

Benchmarking of different navigation sensors. Source: IDTechEx

Collision and proximity sensors

Aside from autonomous mobility, safety always comes as the overarching priority for any robot, especially with increasing human-robot interaction (HRI) and the complexity of tasks. IDTechEx believes that the regulations are expected to get increasingly strict to ensure a high safety level of HRI. In order to make robots comply with the safety requirements, robots need to be able to sense collisions and distances between robots and human operators. When the human operators/objects are in proximity, the robot needs to slow down or stop. To enable this, collision detection and proximity sensors are usually used.

With the advancement of sensor technology, the boundary between collision detection and proximity detection has been blurred. The fundamental difference between collision detection and proximity detection is the distance between the objects and sensors/robots. From the technology point of view, proximity sensors are usually based on one or more of five detection principles that are light reflection, time of flight, triangulation, capacitive, and ultrasonic waves. The chart below compares the different detection principles of several commercial sensors, outlining the response time, and maximum sensing range of each detection method. The general trend here is that robot end-users would want a sensor with a fast response, a large maximum sensing range, and a small footprint. However, depending on certain applications, some factors can be compromised. For instance, indoor autonomous mobile robots for logistics or material handling might not need a sensing range as large as outdoor mobile robots would do.

Comparison of different proximity detection approaches with bubble size indicating the footprint (mm3).

Source: IDTechEx

Summary

Based on the analysis of sensors in 29 robotic applications, IDTechEx concludes that the market will grow very rapidly. Given the large market size of robots and automated machines, IDTechEx believes that the market size of sensors will have a 20-fold increase and exceed $US80 billion within 20 years. Each category of robot and sensor has different needs and market growth. The massive market size and fast growth represent a significant number of opportunities, which are analyzed in detail in the report 'Sensors for Robotics: Technologies, Markets, and Forecasts 2023-2043'.

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EXECUTIVE SUMMARY

1.1.

Overview of the report

1.2.

Overview of sensor yearly sales volume forecast

1.3.

Data table - Yearly sales volume

1.4.

Overview of sensor market size forecast

1.5.

Data table - Market size

1.6.

Key emerging transitions - LiDAR to cameras

1.7.

Comparison of LiDAR, radar, cameras, and 1D/3D ultrasonic sensors

1.8.

Are 3D sensors getting increasingly popular or heading nowhere? (1)

1.9.

Are 3D sensors getting increasingly popular or heading nowhere? (2)

1.10.

Navigation sensors driven by autonomous mobility

1.11.

Collision and proximity sensors gaining momentum - Move towards non-contact sensors? (1)

1.12.

Collision and proximity sensors gaining momentum - Move towards non-contact sensors? (2)

1.13.

Collision detection sensors boom as safety demand enhances - Collision detection sensors forecast (millions)

1.14.

Cameras - Market size forecast by robot type (USD millions)

1.15.

Data table - market size by robot type

1.16.

LiDAR - market size forecast by robot (USD billions)

1.17.

Data table - LiDAR market size

1.18.

Overview of sensor yearly sales volume forecast by sensor type (millions)

1.19.

Market size forecast by sensor type (USD billions)

1.20.

Company Profile Access - IDTechEx Online Portal

INTRODUCTION

2.1.

Sensory system in robots

2.2.

Importance of sensing in robots (1)

2.3.

Importance of sensing in robots (2)

2.4.

Typical sensors used for robots

SENSORS BY FUNCTIONS AND TASKS

3.1.

Sensors by applications

3.2.

Sensor fusion

3.3.

Robotic sensing: why now?

SENSORS FOR NAVIGATION AND MAPPING

4.1.

Navigation and mapping sensors

4.2.

Navigation sensor yearly sales volume forecast (millions)

4.3.

Comparisons of LiDAR, radar, camera & ultrasonic sensors - (1)

4.4.

Comparisons of LiDAR, radar, camera & ultrasonic sensors - (2)

4.5.

Summary of the comparison

4.6.

Navigation sensor fusion - Fixposition AG

4.7.

Technology analysis of Fixposition

4.8.

LiDAR

4.8.1.

LiDAR classifications

4.8.2.

LiDAR Introduction

4.8.3.

Market size forecast of LiDAR by robot type (USD billions)

4.8.4.

Data table

4.8.5.

Comparison with ultrasonic sensors

4.8.6.

3D LiDAR on its way out for indoor mobile robots?

4.8.7.

Performance comparison of different LiDARs on the market or in development - (1)

4.8.8.

Performance comparison of different LiDARs on the market or in development - (2)

4.9.

Camera

4.9.1.

Introduction

4.9.2.

SWOT - RGB/Visible light camera

4.9.3.

Market size forecast - cameras (USD millions)

4.9.4.

Data table - camera market size

4.9.5.

Yearly sales volume forecast - cameras (millions)

4.9.6.

Data table - camera volume

4.9.7.

CMOS image sensors vs CCD cameras for robots

4.9.8.

The emergence of 3D cameras/3D robotic vision

4.9.9.

The emergence of in-camera computer vision in autonomous driving - GEO Semiconductor

4.9.10.

Will AMRs adopt similar in-camera computer vision sensors used in autonomous vehicles?

4.10.

IR Sensor

4.10.1.

Segmenting the electromagnetic spectrum

4.10.2.

SWOT - IR cameras/sensors

4.11.

Hyperspectral imaging sensors

4.11.1.

Introduction to hyperspectral imaging

4.11.2.

Contrasting device architectures for hyperspectral data acquisition

4.11.3.

Line-scan hyperspectral camera design

4.11.4.

Snapshot hyperspectral imaging

4.11.5.

Illumination for hyperspectral imaging

4.11.6.

Hyperspectral imaging as development of multispectral imaging

4.11.7.

Hyperspectral imaging from UAVs (drones)

4.11.8.

Satellite imaging with hyperspectral cameras

4.11.9.

Gamaya: Hyperspectral imaging for agricultural analysis

4.11.10.

Supplier overview: Hyperspectral imaging

4.12.

Radar

4.12.1.

Radar - Radio Detection And Ranging

4.12.2.

Radar anatomy

4.12.3.

Radar key components

4.12.4.

Primary radar components - the antenna

4.12.5.

Primary radar components - the RF transceiver

4.12.6.

Primary radar components - MCU

4.12.7.

Arbe Robotics - High-performance radar with trained deep neural networks

4.12.8.

SWOT of radar

4.12.9.

Radar and LiDAR in robotics

SENSORS FOR COLLISION DETECTION AND SAFETY

5.1.

Overview of sensors for collision detection

5.2.

Force and torque sensors

5.2.1.

Torque sensors - introduction

5.2.2.

Functions required for force sensors in robots

5.2.3.

Market trend of force/torque (F/T) sensors - yearly sales volume (millions)

5.2.4.

Market trend of force/torque (F/T) sensors - market size forecast (USD billions)

5.2.5.

How is a traditional torque sensor made - (1)?

5.2.6.

How is a traditional torque sensor made - (2)?

5.2.7.

What applications need force and torque sensors?

5.2.8.

EPSON quartz crystal piezoelectric force sensors

5.2.9.

Flexible force/pressure sensors used for robotic soft grippers

5.2.10.

Robotic Collision Sensor Protector - ATI Industrial Automation

5.2.11.

Torque and force sensors for robots - overview (1)*

5.2.12.

Torque and force sensors for robots - overview (2)*

5.2.13.

Torque and force sensors for robots - overview (3)*

5.2.14.

Comparison of different torque and force sensors

5.3.

Tactile sensors

5.3.1.

Brief introduction of technologies for tactile sensors in soft grippers

5.3.2.

Piezoresistive vs. Piezoelectric vs. Capacitive technologies

5.3.3.

What are printed piezoresistive sensors?

5.3.4.

What is piezoresistance?

5.3.5.

SWOT: Piezoresistive sensors

5.3.6.

Printed piezoresistive sensors: Anatomy

5.3.7.

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Sensors for Robotics 2023-2043: Technologies, Markets, and Forecasts

Summary

Table of Contents

ご注文は、お電話またはWEBから承ります。お見積もりの作成もお気軽にご相談ください。

本レポートと同分野（センサ・MEMS）の最新刊レポート

IDTechEx社のセンサー - Sensors分野での最新刊レポート

本レポートと同じKEY WORD（）の最新刊レポート

よくあるご質問

IDTechEx社はどのような調査会社ですか?

調査レポートの納品までの日数はどの程度ですか?

注文の手続きはどのようになっていますか?

お支払方法の方法はどのようになっていますか?

データリソース社はどのような会社ですか?