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The market for professional service robots reached a turnover of 6.7 billion U.S. dollars worldwide (sample method) – up 12% in 2020. At the same time, turnover of new consumer service robots grew 16% to 4.4 billion U.S. dollars. This is according to World Robotics 2021 – Service Robots report, presented by the International Federation of Robotics (IFR).

“Service robots continued on a successful path proving the tremendous market potential worldwide,” says IFR President Milton Guerry. “Sales of professional service robots rose an impressive 41% to 131,800 units in 2020.”

Five top application trends for professional service robots were driven by extra demand of the global pandemic:

One out of three units were built for the transportation of goods or cargo. Turnover for Autonomous Mobile Robots (AMR) and delivery robots grew by 11% to over 1 billion US dollars. Most units sold operate in indoor environments for production and warehouses. The trend goes towards flexible solutions, so that the AMR´s act in mixed environments together e.g. with forklifts, other mobile robots or humans. There is also a strong market potential for transportation robots in outdoor environments with public traffic, e.g. lastmile delivery. Marketing and monetarization options will depend on the availability of regulatory frameworks which currently still prevent the large-scale deployment of such robots in most countries.

Demand for professional cleaning robots grew by 92% to 34,400 units sold. In response to increasing hygiene requirements due to the Covid-19 pandemic, more than 50 service robot providers developed disinfection robots, spraying disinfectant fluids, or using ultraviolet light. Often, existing mobile robots were modified to serve as disinfection robots. There is a high ongoing potential for disinfection robots in hospitals and other public places. Unit sales of professional floor cleaning robots are expected to grow by double-digit rates on average each year from 2021 to 2024.

In terms of value, the sales of medical robotics accounts for 55% of the total professional service robot turnover in 2020. This was mainly driven by robotic surgery devices, which are the most expensive type in the segment. Turnover increased by 11% to 3.6 billion U.S. dollars.

A tremendously growing number of robots for rehabilitation and non-invasive therapy make this application the largest medical one in terms of units. About 75% of medical robot suppliers are from North America and Europe.

The global pandemic created additional demand for social robots. They help e.g. residents of nursing homes to keep contact with friends and family members in times of social distancing. Communication robots provide information in public environments to avoid personal human contact, connect people via video for a business conference or help with maintanance tasks on the shopfloor.

Hospitality robots enjoy growing popularity generating turnover of 249 million US dollars. Demand for robots for food and drink preparation grew tremendously – turnover almost tripled to 32 million US dollars (+196%). The Covid-19 pandemic created increased awareness to avoid contact with food products. There is still a huge potential for hospitality robots with medium double-digit annual growth predicted.

Service robots for consumer use

Robots for domestic tasks are the largest group of consumer robots. Almost 18.5 million units (+6%), worth 4.3 billion US dollars, were sold in 2020.

Robot vacuums and other robots for indoor domestic floor cleaning were up 5% to more than 17.2 million units with a value of 2.4 billion US dollar. This kind of service robot is available in almost every convenience store, making it easily accessible for everyone. Many American, Asian, and European suppliers cater to this market.

Gardening robots usually comprise lawn mowing robots. This market is expected to grow by low double-digit growth rates on average each year in the next few years.

Service robotics industry structure

“The service robot industry is developing at a high pace,“ says IFR President Milton Guerry.” “Lots of start-up companies appear every year, developing innovative service robot applications and improving existing concepts. Some of these young companies disappear as quickly as they emerged. The activity remained high in the service robotics space with acquisitions by incumbents and acquisitions by companies from industries with a desire to expand and work in this exciting area.”

Worldwide, 80% of the 1.050 service robot suppliers are considered incumbents that were established more than five years ago. 47% of the service robot suppliers are from Europe, 27% from North America and 25% from Asia.

World Robotics 2021 edition

Orders for World Robotics 2021 Industrial Robots and Service Robots reports can be placed online. Further downloads on the content are available here.

Downloads

Graphs, presentations and German press release are available below:

• Presentation World Robotics press conference extended version (5.9MB)
• Presentation World Robotics press conference short version (8.5MB)
• Graph: TOP 5 applications for professional use (98KB)
• Graph: Service Robot company structure (90KB)
• Overview: TOP Five Service Robot Trends 2021 (202KB)
• Pressemeldung Service Robots auf deutsch (173KB)

By Marco Arruda

This is the 1st chapter of the series “Exploring ROS2 with a wheeled robot”. In this episode, we setup our first ROS2 simulation using Gazebo 11. From cloning, compiling and creating a package + launch file to start the simulation!

You’ll learn:

• How to Launch a simulation using ROS2
• How to Compile ROS2 packages
• How to Create launch files with ROS2

1 – Start the environment

In this series we are using ROS2 foxy, go to this page, create a new rosject selecting ROS2 Foxy distro and and run it.

2 – Clone and compile the simulation

The first step is to clone the dolly robot package. Open a web shell and execute the following:

cd ~/ros2_ws/src/
git clone https://github.com/chapulina/dolly.git


Source the ROS 2 installation folder and compile the workspace:

source /opt/ros/foxy/setup.bash
cd ~/ros2_ws
colcon build --symlink-install --packages-ignore dolly_ignition


Notice we are ignoring the ignition related package, that’s because we will work only with gazebo simulator.

3 – Create a new package and launch file

In order to launch the simulation, we will create the launch file from the scratch. It goes like:

cd ~/ros2_ws/src
ros2 pkg create my_package --build-type ament_cmake --dependencies rclcpp


After that, you must have the new folder my_package in your workspace. Create a new folder to contain launch files and the new launch file as well:

mkdir -p ~/ros2_ws/src/my_package/launch
touch ~/ros2_ws/src/my_package/launch/dolly.launch.py


Copy and paste the following to the new launch file:

import os

from ament_index_python.packages import get_package_share_directory
from launch import LaunchDescription
from launch.actions import DeclareLaunchArgument
from launch.actions import IncludeLaunchDescription
from launch.launch_description_sources import PythonLaunchDescriptionSource

def generate_launch_description():

pkg_gazebo_ros = get_package_share_directory('gazebo_ros')
pkg_dolly_gazebo = get_package_share_directory('dolly_gazebo')

gazebo = IncludeLaunchDescription(
PythonLaunchDescriptionSource(
os.path.join(pkg_gazebo_ros, 'launch', 'gazebo.launch.py')
)
)

return LaunchDescription([
DeclareLaunchArgument(
'world',
default_value=[os.path.join(pkg_dolly_gazebo, 'worlds', 'dolly_empty.world'), ''],
description='SDF world file',
),
gazebo
])


Notice that a launch file returns a LaunchDescription that contains nodes or other launch files.

In this case, we have just included another launch file gazebo.launch.py and changed one of its arguments, the one that stands for the world name: world.

The robot, in that case, is included in the world file, so there is no need to have an extra spawn node, for example.

And append to the end of the file ~/ros2_ws/src/my_package/CMakeLists.txt the following instruction to install the new launch file into the ROS 2 environment:

install(DIRECTORY
launch
DESTINATION share/${PROJECT_NAME}/
)

ament_package()


4 – Compile and launch the simulation

Use the command below to compile only the created package:

cd ~/ros2_ws/
colcon build --symlink-install --packages-select my_package
source ~/ros2_ws/install/setup.bash
ros2 launch my_package dolly.launch.py


5 – Conclusion

This is how you can launch a simulation in ROS2. It is important to notice that:

• We are using a pre-made simulation: world + robot
• This is how a launch file is created: A python script
• In ROS2, you still have the same freedom of including other files or running executables inside a custom launch file

Related courses & extra links:

• ROS2 Basics for C++
• Copy my rosject here
• Dolly robot – Official repo

Exoskeletons have remarkable potential. As with their science fiction counterparts, these machines can amplify their users’ strength, letting them lift heavier objects with less effort.

Robots can deliver food on a college campus and hit a hole in one on the golf course, but even the most sophisticated robot can't perform basic social interactions that are critical to everyday human life.

For people with motor impairments or physical disabilities, completing daily tasks and house chores can be incredibly challenging. Recent advancements in robotics, such as brain-controlled robotic limbs, have the potential to significantly improve their quality of life.

A robotic boat has been used for the first time to survey fish populations around oil platforms in the North Sea.

From pick-and-pack to palletization, Master's Gallery Foods relies on flexible robotics systems from Quest Industrial to streamline end-of-line packaging throughput at its six Wisconsin cheese maturation facilities.

The sheer expanse of the deep sea and the technological challenges of working in an extreme environment make these depths difficult to access and study. Scientists know more about the surface of the moon than the deep seafloor. MBARI is leveraging advancements in robotic technologies to address this disparity.

Over the past decade or so, many roboticists and computer scientists have been trying to develop robots that can complete tasks in spaces populated by humans; for instance, helping users to cook, clean and tidy up. To tackle household chores and other manual tasks, robots should be able to solve complex planning tasks that involve navigating environments and interacting with objects following specific sequences.

The camera control, which gives the robot the flexibility for an infinite variety of parts, and the EasyControl graphical user interface with its easy-to-understand input screens that allow users to automate without any robot knowledge.

Picking up a blueberry or grape without squishing it isn't hard, but try teaching it to a robot. The same goes for walking on ice, turning a key to unlock a door or cooking a favorite dish.

In this episode, Audrow Nash speaks to Tobias Holmes, Quality Assurance Manager at Blue River Technologies. Blue River uses computer vision and robotics in agriculture and was acquired by John Deere in 2017. Tobias speaks about herbicide resistance, spraying weeds, quality assurance and testing on hardware, and on encouraging kids to learn robotics.

 

Episode Links

• Download the episode
• Tobias’ LinkedIn
• Blue River Technology
• FIRST Robotics
• Crystal Ray High School (East Bay)

Podcast info

• Podcast website
• Apple Podcasts
• Spotify
• RSS
• Full episodes on YouTube

Researchers from the Institute of Engineering and Technology at the Nicolaus Copernicus University have developed an algorithm that will allow mobile robots to escape blind alleys and avoid obstacles.

Currently, most robots are seen in industry where they support repetitive tasks, such as in the assembly lines of cars or in the production of microchips. However, in the near future the robot should find his way in less structured environments as well, to be able to work in healthcare or in hazardous environments, such as disaster areas. Researcher Wouter Houtman investigated the interaction of robots with their environment and developed algorithms to improve their movements in "the real world." He will defend his Ph.D. thesis at the department of Mechanical Engineering on Thursday 4th of November.

Boosting efficiency through digitalization - almost no branch of industry can evade it. Also operators of press shops are increasingly networking their production. But - it's not always necessary to replace the entire plant in order to stay up to date.