Le chiffre d'affaires annuel des capteurs de l'industrie robotique dépassera les 80 milliards de dollars américains d'ici 2043.

Capteurs pour la robotique 2023-2043 : technologies, marchés et prévisions

Une évaluation technologique et commerciale des capteurs utilisés dans les robots par type de capteur et applications. Robots mobiles, drones, bras robotiques industriels, cobots et robots de service. Types de capteurs, notamment force/couple, proximité, caméras, LiDAR, etc.

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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
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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Table of Contents
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
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
3.1.Sensors by applications
3.2.Sensor fusion
3.3.Robotic sensing: why now?
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
4.8.1.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 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)
4.9.2.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
4.12.1.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
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.Pressure sensing architectures
5.3.8.Shunt mode sensors
5.3.9.Capacitive proximity and tactile sensors - AIDIN Robotics
5.4.Proximity sensor
5.4.1.Introduction of detection principle of proximity sensors
5.4.2.Explanation of basic terms
5.4.3.Light reflection method - introduction
5.4.4.Capacitance method (capacitive proximity sensors)
5.4.5.Capacitive proximity sensor and ToF sensor in robots
5.4.6.Triangulation method
5.4.7.Time-of-flight (ToF) sensors
5.4.8.Ultrasonic methods
5.4.9.Ultrasonic sensors ultrasonic sensors - Topsens
5.4.11.Ultrasonic sensors - yearly sales volume forecast (thousands)
5.4.12.Optical encoders
5.4.13.Comparison of proximity sensors
5.4.14.Capacitive sensors
5.4.15.Challenges in e-skins - high power consumption and computational power required
6.1.Accelerometer, gyroscope sensor, and IMU
6.2.IMU, ultrasonic sensors and GPS sensors
6.3.IMU market trend - yearly sales volume forecast (millions)
6.4.Example - LORD Sensing 3DM-GX5 - IMU and altimeter
6.5.Sensors for servo motors
6.6.Microelectromechanical systems (MEMS) pressure sensors
6.7.Texas Instruments and TE Connectivity
6.8.Pressure sensors for drones - yearly sales volume forecast (millions)
6.9.Altimeter - (1)
6.10.Altimeter - (2)
6.11.Bosch Sensortec
6.13.Altimeter for drones - yearly sales volume forecast (millions)
7.2.The overall scope of all the use cases
7.3.Sensors for industrial robotic arms
7.3.1.What are industrial robots and what does the current market look like?
7.3.2.Types of sensors in industrial robotic arms - overview
7.3.3.Forecast overview - sensors for industrial robotic arms - yearly sales volume (millions)
7.3.4.Safety sensors - safety light curtains (SLCs) - photoelectric sensors
7.3.5.Benefits of safety light curtains - photoelectric sensors
7.3.6.Photoelectric sensors yearly sales volume forecast (millions)
7.3.7.Force sensors and vision sensors
7.4.Sensors for AGV and AMR
7.4.1.Sensors for AGV and AMR - overview
7.4.2.Forecast overview - sensors for AGV and AMR - yearly sales volume (millions)
7.4.3.Forecast overview - sensors for AGV and AMR - market size (USD billions)
7.4.4.Comparison of navigation sensors for autonomous robots
7.4.5.Sensors for object detection
7.4.6.Case study - Omron LD series
7.4.7.Case study - Omron HD series
7.4.8.Autonomous driving example - Nuro
7.4.9.Other autonomous driving vehicles with LiDAR
7.4.10.LiDAR drawbacks and transitions to cameras
7.4.11.LiDAR - how will they change in the future?
7.4.12.Mobile robot example - MiR
7.4.13.Summary of typical sensors and their applications in commercial mobile robots
7.5.Sensors for collaborative robots (cobots)
7.5.1.Cobot - functions and typical sensors
7.5.2.Forecast overview - yearly sales volume of sensors for cobots (millions)
7.5.3.Cobot example - Kawasaki Robotics
7.5.4.Capacitive proximity and tactile sensors - AIDIN Robotics
7.5.5.Market trend of cobot tactile sensors - yearly sales volume (thousands)
7.5.6.Time-of-flight (ToF) sensors
7.5.7.Challenges with traditional force sensors
7.5.8.Force sensing - FRANKA EMIKA
7.5.9.Robotic visual and force sensing
7.5.10.Torque sensors
7.5.11.Vision systems for cobots
7.6.Sensors for drones
7.6.1.Overview of the sensors in drones (1)
7.6.2.Market trend of drone sensors - yearly sales volume forecast (millions)
7.6.3.Riegl - LiDAR sensor for unmanned laser scanning
7.6.4.LightWare - lightest and smallest LiDAR
7.6.6.Radar in agriculture - Sarmap
7.6.7.Octopus ISR System - a division of Edge Autonomy
7.6.8.DST Control - Gyro-stabilized gimbal
7.6.9.IMU for pose estimation - DJI
7.7.Sensors for service robots
7.7.1.Overview for sensors for service robots
7.8.Sensors for underwater robots
7.8.1.Challenges in the sensing systems of underwater robots
7.8.2.Key technologies - sensing and navigation
7.8.3.Sensors for underwater robots (1)
7.8.4.Sensors for underwater robots (2)
7.8.5.Navigation and localization technologies
7.8.6.Localization and navigation for underwater robots
7.8.8.Localisation and navigation for underwater robots
7.9.Sensors in agricultural robots
7.9.1.Overview of sensors and tasks for agricultural robots
7.9.2.Market trend of sensors in agricultural robots - yearly sales volume forecast (thousands)
7.9.3.Market trend of sensors in agricultural robots - data table
7.9.4.Agricultural drones - imaging sensors comparison
7.9.5.Navigation sensors in agricultural robots
7.9.6.Challenges of RTK-GPS sensors in agricultural robots
7.10.Sensors in cleaning and disinfection robots
7.10.1.Cleaning robots - overview of tasks and sensors
7.10.2.Market trend of cleaning robots - yearly sales volume (millions)
7.10.3.Sensors in cleaning robots
7.10.4.Audite Robotics - LiDAR for mapping
7.10.5.SWOT - Audite
7.10.6.Sensors in social robots - overview
7.11.Sensors in social robots
7.11.1.Market trend of social robots - yearly sales volume forecast (millions)
7.11.2.Trend in sensing technologies for social robots
7.11.3.Emerging sensors for social robots - Softbank Pepper
7.11.4.Touch sensors - capacitive touch sensing technologies introduction - LOVOT
7.11.5.Capacitive sensors: Operating principle
7.11.6.Hybrid capacitive / piezoresistive sensors
7.11.7.Emerging current mode sensor readout: Principles
7.11.8.SWOT analysis of capacitive touch sensors
7.11.9.The potential trend in social robots - haptic feedback
7.12.Forecast Summary
7.12.1.Overview of common sensors in different applications - yearly sales volume (millions)
7.12.2.Data table - yearly sales volume
7.12.3.Overview of common sensors in different applications - market size (USD billions)
7.12.4.Data table - market size
7.12.5.Autonomous navigation and localization in robots
7.12.6.Navigation sensors by robot type - yearly sales volume forecast (millions)
7.12.7.Data table - navigation sensors
7.12.8.Navigation sensors sales for robots will be 22 times more than today - yearly sales volume (millions)
7.12.9.Navigation sensors - market size forecast (USD billions)
7.12.10.Collision detection sensors have 17-fold increase compared with 2022 - yearly sales volume forecast (millions)
7.12.11.Collision detection sensors - market size forecast (USD billions)
7.12.12.Sensors by robot type - yearly sales volume forecast (millions)
7.12.13.Data table - volume
7.12.14.Sensors by robot type - market size (USD billions)
7.12.15.Data table - market size
8.1.Aidin Robotics
8.4.Audite Robotics
8.5.ClearPath Robotics
8.6.Clearview Imaging
8.8.F&P Personal Robotics
8.9.Franka Emika
8.11.Interlink Electronics
8.14.Neura Robotics
8.17.Pal Robotics
8.23.TE Connectivity
8.24.Techman Robot
8.25.Universal Robots
8.29.Yujin Robot

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Slides 251
Forecasts to 2043
ISBN 9781915514387

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