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Top 10 ROS-based robotics companies in 2019

Top 10 ROS-based robotics companies in 2019

Source: Ricardo Tellez

The Robot Operating System is becoming the standard in robotics, not only for robotics research, but also for robotics companies that build and sell robots. In this article, I offer a list of the top 10 robotics companies worldwide that base their robotics products on ROS.

Criteria

This is the list of criteria I followed to select the winners:

  • We are talking about robotics companies that build robots. This is not about companies that produce some kind of software based in ROS, but companies that create and ship robots based in ROS. We do not consider companies that do consulting and generate solutions for a third party, either.
  • They have created the robots themselves. This means they are not resellers or distributors of robots made by somebody else.
  • They have their robots natively running ROS. This means, you switch the robot on, and it is running ROS. We are not taking into account robots that support ROS — if you install the packages. We concentrate on robots that run ROS off the shelf. For example, you can run ROS on a UR5 arm robot, but if you buy the UR5 robot, it will not come with ROS support off the shelf. You need to add an extra layer of work. We are not considering those robots.
  • You can program the robots. Even if some companies provide ROS-based robots — such as Locus Robotics — they do not provide a way to program them. They provide the robots as a closed solution. We are not considering closed solutions here.

To summarize the criteria: 1. You can buy the robot directly from the company; 2. The robot runs ROS from Minute 1; and 3. You can program the robot at will.

Once the companies were selected based on the previous criteria, I had to decide the order. Order was based on my personal perception of the impact those companies are making in the ROS world. That is very subjective to my own experience, I know, but that is what it is. Whenever I felt it necessary, I described my motivation behind the position of the company on the list.

Now, having clarified all that, let’s go to the list!

Top 10 ROS companies

1. Clearpath Robotics

Clearpath is a Canadian company founded in 2009. The number of robots that it produces in the fields of unmanned ground vehicles, unmanned surface vehicles (on the water), and industrial vehicles is amazing. The company’s robots are based on ROS and can be programmed with ROS from Minute 1. That is why these robots are used in the creation of third-party applications for mining, survey, inspection, agriculture, and material handling.

Some of Clearpath’s best-known robots include Jackal UGV, which you can learn how to program. Others include the Husky UGV, Heron USV, and its recently launched series of Otto robots for industrial environments.

As a matter of trustability, this company took the responsibility to provide the customer support to the existing PR2 robots, once Willow Garage closed its doors. Because of that, and because it is the company with the most varied ROS robots available, I put it in the well-deserved No. 1 spot on this list.

I interviewed Ryan Gariepy, CTO of Clearpath, for the ROS Developers podcast. You can listen to the interview here.

2. Fetch Robotics

Fetch Robotics was founded by Melonee Wise in 2014, after she was forced to close her previous pioneer company, Unbounded Robotics. We can say that Fetch has two lines of business. First is its line of mobile manipulators, which are mainly used for robotics research.

Then, Fetch has a line of industrial robots which it sells in fleets ready to be deployed in a warehouse to help with the transport of materials. As I understand it, the first line of business is the only one that allows direct ROS programming, and the second one is a closed product.

I did not select Fetch for No. 2 because of its research line only. I selected it for this spot because Fetch was a pioneer in the creation of affordable mobile manipulators with its Fetch robot (paired with the Freight mobile platform). Up to the moment it released Fetch, there was no ROS-based mobile manipulator on the market. (Sorry, Turtlebot 2 with a Dynamixel arm doesn’t count as a mobile manipulator.)

Recently, Fetch organized the FetchIt! challenge at ICRA 2019. (My company, The Construct, was a partner contributing to the event’s simulation.) At that event, participants had to program their Fetch to produce some pieces in a manufacturing room. You can check the results here.

Even if Fetch Robotics only produces two robots meeting the criteria above, it was the pioneer that opened the field of ROS-based mobile manipulators. That is why it deserves the No. 2 spot on this list.

I interviewed Melonee Wise, CEO of Fetch Robotics, for the ROS Developers podcast. You can listen to the interview here.

3. Pal Robotics

Pal Robotics is based in Barcelona and was created in 2004. I especially love Pal because I worked there for more than seven years, and many of my friends are there. But love is not the reason I put them in the third position.

Pal Robotics earned No. 3 because it’s the only company in the world that builds and sells human-size humanoid robots. And not just a single type of humanoid, but three different types! The Reem robot, Reem-C robot, and recently, the TALOS robot.

Pal also produces mobile manipulators similar to the Fetch ones. They are called Tiago, and you can buy them for your research or applications on top. (If you’re interested, you can learn how to program Tiago robots with ROS in an online course that The Construct created in collaboration with Pal Robotics.)

We have recently released a simulation of TALOS, including its walking controllers. You can get it here.

I interviewed Luca Marchionni, CTO of Pal Robotics, for the ROS Developers podcast. You can listen to the interview here. Also, you can learn what is catkin_make and how to use it.

In addition, I interviewed Victor Lopez, main DevOps engineer of Pal Robotics, for the ROS Developers podcast. You can listen to that interview here.

4. Robotnik

Robotnik is another Spanish company, based in Castellon and founded in 2002. I call it “the Spanish Clearpath.” Really, it has built as many ROS robots as the first company on this list. Robotnik creates and designs mobile manipulators, unmanned ground vehicles of different types, and many types of mobile robots for industrial applications and logistics.

The company is also expert in personalizing your robot by integrating third-party robotics parts into a final ROS-based robot that meets your requirements.

Finally, Robotnik’s team includes the people behind the ROS Components online shop, where you can buy components for your robots that are certified to be ROS supported off the shelf. For all this extensive activity in selling ROS robots, Robotnik deserves the fourth position on this list.

A couple of months ago, Robotnik sent us one of its Summit XL robots for experimenting and creating ROS training materials. We used it extensively for our ROS Live Classes, showing how to program Robotinik robots using a cloud robotics platform.

We also created a specific course to train people to program their Summit XL robot.

I interviewed Roberto Martinez, CEO of Robotnik, for the ROS Developers podcast. You can listen to the interview here.

5. Yujin Robots

Yujin is a Korean company specializing in vacuum cleaning robots. However, those robots are not the reason they are on this list, since they do not run ROS onboard. Instead, Yujin is here because it’s the official seller of the Kobuki robot, that is, the base system of the Turtlebot 2 robot.

The Turtlebot 2 is the most famous ROS robot in the world, even more so than the PR2! Almost every one of us has learned with that robot, either in simulation or in reality. Due to its low cost, it allows you to easily enter into the ROS world.

If you have bought a Turtlebot 2 robot, it is very likely that the base was made by Yujin. We used Kobuki as the base of our robot Barista, and I use several of them at my ROS class at La Salle University.

Additionally, Yujin has developed another ROS robot for logistics that is called GoCart, a very interesting robot for logistics inside buildings (but not warehouses). The robot can be used to send packages from one location in the building to another — including elevators on the path.

6. Robotis

This is another Korean company that is making it big in the ROS world. Even if Robotis is well known for its Dynamixel servos, it’s best known in the ROS world because of its Turtlebot 3 robot and Open manipulator, both presented as the next generation of the Turtlebot series.

With the development of the Turtlebot 3, Robotis brought the Turtlebot concept to another level, allowing people easier entry into ROS. The manipulator is also very well integrated with the Turtlebot 3, so you can have a complete mobile manipulator for a few hundred dollars.

Even easier, the company has made all the designs of both robots open-source, so you can build the robots yourself. Here are the designs of Turtlebot 3. Here are the designs of Open Manipulator.

7. Shadow Robot

Shadow Robot is based in London. This company is a pioneer in the development of humanoid robotic hands. To my knowledge, Shadow Robot is the only company in the world that sells that kind of robotic hand.

Furthermore, its hands are ROS-programmable off the shelf. Apart from hands, Shadow Robot also produces many other types of grippers, which can be mounted on robotic arms to create complete grasping solutions.

One of its solutions combined with third-party robots was the Smart Grasping System released in 2016. It compbined a three-fingered gripper with a UR5 robot. Hhere is a simulation we created of the Smart Grasping System, in collaboration with Ugo Cupcic.

Shadow Robot’s products include the Shadow Hand, the Cyberglobe, and the Tactile telerobot.

Demonstrating its leadership in the field, Shadow Robot’s hands were selected by the OpenAI company to do their reinforcement learning experiments with robots that need to learn dexterity.

8. Husarion

Husarion is a Polish company founded in 2013. It sells simple and compact autonomous mobile robots called ROSbots. They are small, four-wheeled robots equipped with a lidar, camera, and a point cloud device. These robots are perfect for learning ROS with a real robot, or for doing research and learning with a more compact robot than the Turtlebot 2.

Husarion also produces the Panther robot, which is more oriented to outdoor environments, but with the same purpose of research and learning.

What makes Husarion different from other companies selling ROS robots is the compactness of its robots and its creation of the Husarnet network, which connects the robots through the cloud and has remote control over them.

I interviewed Dominik Novak, CEO of Husarion for the ROS Developers podcast. You can listen to the interview here.

9. Neobotix

Neobotix is a manufacturer of mobile robots and robot systems in general. It provides robots and manipulators for a wide range of industrial applications, especially in the sector of transporting material.

Neobotix is a spin-off of the Fraunhofer Institute in Stuttgart, and it created the famous Care-O-Bot, used many times in the Robocup@Home competitions. However, as far as I know, the Care-O-Bot never reached the point of product, even if you can order five of them and get them delivered, running immediately after unpacking.

At present, Neobotix is focusing on selling mobile bases, which can be customized with robotics arms, converting the whole system in a custom mobile manipulator.

The company also sells the mobile bases and the manipulators separately. Examples of mobile bases include Neobotix’s MP series of robots. On the mobile manipulator side, it sells the MM series. All of them work off-the-shelf with ROS.

Even if Neobotix’s products are full products on their own, I see them more as components that we can use for building more complex robots, allowing us to save time creating all the parts. That is why I have decided to put it in the ninth position and not above the other products.

10. Gaitech

Gaitech is a Chinese company that is mainly dedicated to distributing ROS robots, and ROS products in general, in China. from third-party companies. They include many of the companies on this list, including Fetch, Pal, and Robotnik.

However, Gaitech has also developed its own line of robots. For example, the Gapter drone is the only drone I’m aware of that works with ROS off the shelf.

Even if Gaitech’s robots are not very popular in the ROS circuit, I have included them it because at present, it’s the only company in the world that is building ROS–based drones. (Erle Robotics did ROS-based drones in the past, but as far as I know, that ceased when it switched to Acutronic Robotics.) Due to this lack of competition, I think Gaitech deserves the No. 10 position.

I interviewed May Zheng, VP of Marketing of Gaitech, for the ROS Developers podcast. You can listen to the interview here.

Honorable mentions

The following is a shortlist of other companies building ROS robots that did not make it onto the list for certain reasons. They may be here next year!

1. Sony

Sony is a complete newcomer to the world of ROS robots, but it has entered through the big door. Last year, it announced the release of the Aibo robot dog, which fully works on ROS. That was a big surprise to all of us, especially since Sony abandoned the Aibo project back in 2005.

Sony’s revived robot dog could have put it on the list above, except for the fact that the robot is still too new and can only be bought in the U.S. and Japan. Furthermore, the robot still has a very limited programming SDK, so you can barely program it.

If you are interested in the inner workings of Aibo with ROS, have a look at the presentation by Tomoya Fujita, one of the engineers of the project, during the ROS Developers Conference 2019, where he explained the communication mechanism between processes that they had to develop for ROS in order to reduce battery consumption in Aibo. Amazing stuff, fully compatible with ROS nodes and using the standard communication protocol!

2. Ubiquity Robotics

This is a company based on selling simple mobile bases based on ROS for the development of third-party solutions, or as it calls them, “robot applications.” Ubiquity Robotics’ goal is to provide a solid mobile base with off-the-shelf navigation on top of which you can build other solutions like telepresence, robotic waiters, and so on.

Ubiquity Robotics is a young company with a good idea in mind, but it’s very close to existing solutions like Neobotix or Robotnik. Let’s see next year how they have evolved.

I interviewed David Crawley, CEO of Ubiquity, for the ROS Developers podcast. You can listen to the interview here.

3. Acutronic Robotics

This company started building ROS-based drones, but recently, they changed direction to produce hardware ROS microchips. Acutronic produces the MARA robot, an industrial arm based on ROS2 on the H-ROS microchips.

However, as far as I know, the MARA robot is not Acutronics’ main business, since the company created it and sells it as an example of what can be done with H-ROS. That is why I decided not to include this company in the main top 10 list.

By the way, we also collaborated with Acutronic to create a series of videos about how to learn ROS2 using their MARA robot.

I interviewed Victor Mayoral, CEO of Acutronic, for the ROS Developers podcast. You can listen to the interview here.

ROS conclusions

Most of the ROS-based robotics companies are based on wheeled robots. A few exceptions are the humanoid robots of Pal Robotics, the drones of Gaitech, the robotic hands from Shadow Robots, and the robot arms from Neobotix.

It’s very interesting that we see almost no drones and no robotic arms running ROS off the shelf, since both of them are very basic types of robots. There are many robotic arm companies that provide ROS drivers for their robots and many packages for their control, like Universal Robots or Kinova.

But of the listed companies, only Neobotix actually provides an off-the-shelf arm robot with its MM series. I think there is a lot of market space for new ROS-based drones and robotic arms. Take note of that, entrepreneurs of the world!

Finally, I would like to acknowledge that I do not know all the ROS companies out there. Even if I have done my research to create this article, I may have missed some companies worth mentioning. Let me know if you know of or have a company that sells ROS robots and should be on this list, so I can update it and correct any mistakes.

Ricardo Tellez

About the author

Ricardo Tellez is co-founder and CEO of The Construct. Prior to this role, he was a postdoctoral researcher at the Robotics Institute of the Spanish Research Council. Tellez worked for more than seven years at Pal Robotics developing humanoid robots, including its navigation system and reasoning engine. He holds a Ph.D. in artificial intelligence and aims to create robots that really understand what they are doing. Tellez spoke at the 2019 Robotics Summit & Expo in Boston.

The post Top 10 ROS-based robotics companies in 2019 appeared first on The Robot Report.

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Velodyne Lidar acquires Mapper.ai for advanced driver assistance systems

SAN JOSE, Calif. — Velodyne Lidar Inc. today announced that it has acquired Mapper.ai’s mapping and localization software, as well as its intellectual property assets. Velodyne said that Mapper’s technology will enable it to accelerate development of the Vella software that establishes its directional view Velarray lidar sensor.

The Velarray is the first solid-state Velodyne lidar sensor that is embeddable and fits behind a windshield, said Velodyne, which described it as “an integral component for superior, more effective advanced driver assistance systems” (ADAS).

The company provides lidar sensors for autonomous vehicles and driver assistance. David Hall, Velodyne’s founder and CEO invented real-time surround-view lidar systems in 2005 as part of Velodyne Acoustics. His invention revolutionized perception and autonomy for automotive, new mobility, mapping, robotics, and security.

Velodyne said its high-performance product line includes a broad range of sensors, including the cost-effective Puck, the versatile Ultra Puck, and the autonomy-advancing Alpha Puck.

Mapper.ai staffers to join Velodyne

Mapper’s entire leadership and engineering teams will join Velodyne, bolstering the company’s large and growing software-development group. The talent from Mapper.ai will augment the current team of engineers working on Vella software, which will accelerate Velodyne’s production of ADAS systems.

Velodyne claimed its technology will allow customers to unlock advanced capabilities for ADAS features, including pedestrian and bicycle avoidance, Lane Keep Assistance (LKA), Automatic Emergency Braking (AEB), Adaptive Cruise Control (ACC), and Traffic Jam Assist (TJA).

“By adding Vella software to our broad portfolio of lidar technology, Velodyne is poised to revolutionize ADAS performance and safety,” stated Anand Gopalan, chief technology officer at Velodyne. “Expanding our team to develop Vella is a giant step towards achieving our goal of mass-producing an ADAS solution that dramatically improves roadway safety.”

“Mapper technology gives us access to some key algorithmic elements and accelerates our development timeline,” Gopalan added. “Together, our sensors and software will allow powerful lidar-based safety solutions to be available on every vehicle.”

Mapper.ai to contribute to Velodyne software

Mapper.ai developers will work on the Vella software for the Velarray sensor. Source: Velodyne Lidar

“Velodyne has both created the market for high-fidelity automotive lidar and established itself as the leader. We have been Velodyne customers for years and have already integrated their lidar sensors into easily deployable solutions for scalable high-definition mapping,” said Dr. Nikhil Naikal, founder and CEO of Mapper, who is joining Velodyne. “We are excited to use our technology to speed up Velodyne’s lidar-centric software approach to ADAS.”

In addition to ADAS, Velodyne said it will incorporate Mapper technology into lidar-centric solutions for other emerging applications, including autonomous vehicles, last-mile delivery services, security, smart cities, smart agriculture, robotics, and unmanned aerial vehicles.

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TIAGo++ robot from PAL Robotics ready for two-armed tasks

Among the challenges for developers of mobile manipulation and humanoid robots is the need for an affordable and flexible research platform. PAL Robotics last month announced its TIAGo++, a robot that includes two arms with seven degrees of freedom each.

As with PAL Robotics‘ one-armed TIAGo, the new model is based on the Robot Operating System (ROS) and can be expanded with additional sensors and end effectors. TIAGo++ is intended to enable engineers to create applications that include a touchscreen interface for human-robot interaction (HRI) and require simultaneous perception, bilateral manipulation, mobility, and artificial intelligence.

In addition, TIAGo++ supports NVIDIA’s Jetson TX2 as an extra for machine learning and deep learning development. Tutorials for ROS and open-source simulation for TIAGo are available online.

Barcelona, Spain-based PAL, which was named a “Top 10 ROS-based robotics company to watch in 2019,” also makes the Reem and TALOS robots.

Jordi Pagès, product manager of the TIAGo robot at PAL Robotics responded to the following questions about TIAGo++ from The Robot Report:

For the development of TIAGo++, how did you collect feedback from the robotics community?

Pagès: PAL Robotics has a long history in research and development. We have been creating service robotics platforms since 2004. When we started thinking about the TIAGo robot development, we asked researchers from academia and industry which features would they expect or value in a platform for research.

Our goal with TIAGo has always been the same: to deliver a robust platform for research that easily adapts to diverse robotics projects and use cases. That’s why it was key to be in touch with the robotics and AI developers from start.

After delivering the robots, we usually ask for feedback and stay in touch with the research centers to learn about their activities and experiences, and the possible improvements or suggestions they would have. We do the same with the teams that use TIAGo for competitions like RoboCup or the European Robotics League [ERL].

At the same time, TIAGo is used in diverse European-funded projects where end users from different sectors, from healthcare to industry, are involved. This allows us to also learn from their feedback and keep finding new ways in which the platform could be of help in a user-centered way. That’s how we knew that adding a second arm into the TIAGo portfolio of its modular possibilities could be of help to the robotics community.

How long did it take PAL Robotics to develop the two-armed TIAGo++ in comparison with the original model?

Pagès: Our TIAGo platform is very modular and robust, so it took us just few months from taking the decision to having a working TIAGo++ ready to go. The modularity of all our robots and our wide experience developing humanoids usually helps us a lot in reducing the redesign and production time.

The software is also very modular, with extensive use of ROS, the de facto standard robotics middleware. Our customers are able to upgrade, modify, and substitute ROS packages. That way, they can focus their attention on their real research on perception, navigation, manipulation, HRI, and AI.

How high can TIAGo++ go, and what’s its reach?

Pagès: TIAGo++ can reach the floor and up to 1.75m [5.74 ft.] high with each arm, thanks to the combination of its 7 DoF [seven degrees of freedom] arms and its lifting torso. The maximum extension of each arm is 92cm [36.2 in.]. In our experience, this workspace allows TIAGo to work in several environments like domestic, healthcare, and industry.

TIAGo++ robot from PAL Robotics

The TIAGo can extend in height, and each arm has a reach of about 3 ft. Source: PAL Robotics

What’s the advantage of seven degrees of freedom for TIAGo’s arms over six degrees?

Pagès: A 7-DoF arm is much better in this sense for people who will be doing manipulation tasks. Adding more DoFs means that the robot can arrive to more poses — positions and orientations — of its arm and end-effector that it couldn’t reach before.

Also, this enables developers to reduce singularities, avoiding non-desired abrupt movements. This means that TIAGo has more possibilities to move its arm and reach a certain pose in space, with a more optimal combination of movements.

What sensors and motors are in the robot? Are they off-the-shelf or custom?

Pagès: All our mobile-based platforms, like the TIAGo robot, combine many sensors. TIAGo has a laser and sonars to move around and localize itself in space, an IMU [inertial measurement unit], and an RGB-D camera in the head. It can have a force/torque sensor on the wrist, especially useful to work in HRI scenarios. It also has a microphone and a speaker.

TIAGo has current sensing in every joint of the arm, enabling a very soft, effortless torque control on each of the arms. The possibility of having an expansion panel with diverse connectors makes it really easy for developers to add even more sensors to it, like a thermal camera or a gripper camera, once they have TIAGo in their labs.

About the motors, TIAGo++ makes use our custom joints integrating high-quality commercial components and our own electronic power management and control. All motors also have encoders to measure the current motor position.

What’s the biggest challenge that a humanoid like TIAGo++ can help with?

Pagès: TIAGo++ can help with are those tasks that require bi-manipulation, in combination with navigation, perception, HRI, or AI. Even though it is true that a one-arm robot can already perform a wide range of tasks, there are many actions in our daily life that require of two arms, or that are more comfortably or quickly done with two arms rather than one.

For example, two arms are good for grasping and carrying a box, carrying a platter, serving liquids, opening a bottle or a jar, folding clothes, or opening a wardrobe while holding an object. In the end, our world and tools have been designed for the average human body, which is with two arms, so TIAGo++ can adapt to that.

As a research platform based on ROS, is there anything that isn’t open-source? Are navigation and manipulation built in or modular?

Pagès: Most software is provided either open-sourced or with headers and dynamic libraries so that customers can develop applications making use of the given APIs or using the corresponding ROS interfaces at runtime.

For example, all the controllers in TIAGo++ are plugins of ros_control, so customers can implement their own controllers following our public tutorials and deploy them on the real robot or in the simulation.

Moreover, users can replace any ROS package by their own packages. This approach is very modular, and even if we provide navigation and manipulation built-in, developers can use their own navigation and manipulation instead of ours.

Did PAL work with NVIDIA on design and interoperability, or is that an example of the flexibility of ROS?

Pagès: It is both an example of how easy is to expand TIAGo with external devices and how easy is to integrate in ROS these devices.

One example of applications that our clients have developed using the NVIDIA Jetson TX2 is the “Bring me a beer” task from the Homer Team [at RoboCup], at the University of Koblenz-Landau. They made a complete application in which TIAGo robot could understand a natural language request, navigate autonomously to the kitchen, open the fridge, recognize and select the requested beer, grasp it, and deliver it back to the person who asked for it.

As a company, we work with multiple partners, but we also believe that our users should be able to have a flexible platform that allows them to easily integrate off-the-shelf solutions they already have.

How much software support is there for human-machine interaction via a touchscreen?

Pagès: The idea behind integrating a touchscreen on TIAGo++ is to bring customers the possibility to implement their own graphical interface, so we provide full access to the device. We work intensively with researchers, and we provide platforms as open as our customers need, such as a haptic interface.

What do robotics developers need to know about safety and security?

Pagès: A list of safety measures and best practices are provided in the Handbook of TIAGo robot in order that customers ensure safety both around the robot and for the robot itself.

TIAGo also features some implicit control modes that help to ensure safety while operation. For example, an effort control mode for the arms is provided so that collisions can be detected and the arm can be set in gravity compensation mode.

Furthermore, the wrist can include a six-axis force/torque sensor providing more accurate feedback about collisions or interactions of the end effector with the environment. This sensor can be also used to increase the safety of the robot. We provide this information to our customers and developers so they are always aware about the safety measures.

Have any TIAGo users moved toward commercialization based on what they’ve learned with PAL’s systems?

Pagès: At the moment, from the TIAGo family, we commercialize the TIAGo Base for intralogistics automation in indoor spaces such as factories or warehouses.

Some configurations of the TIAGo robot have been tested in pilots in healthcare applications. In the EnrichMe H2020 EU Project, the robot gave assistance to old people at home autonomously for up to approximately two months.

In robotics competitions such as the ERL, teams have shown the quite outstanding performance of TIAGo in accomplishing specific actions in a domestic environment. Two teams ended first and third in the RoboCup@Home OPL 2019 in Sydney, Australia. The Homer Team won for the third time in a row using TIAGo — see it clean a toilet here.

The CATIE Robotics Team ended up third in the first world championship in which it participated. For instance, in one task, it took out the trash.

The TIAGo robot is also used for European Union Horizon 2020 experiments in which collaborative robots that combine mobility with manipulation are used in industrial scenarios. This includes projects such as MEMMO for motion generation, Co4Robots for coordination, and RobMoSys for open-source software development.

Besides this research aspect, we have industrial customers that are using TIAGo to improve their manufacturing procedures.

How does TIAGo++ compare with, say, Rethink Robotics’ Baxter?

Pagès: With TIAGo++, besides the platform itself, you also get support, extra advanced software solutions, and assessment from a company that continues to be in the robotics sector since more than 15 years ago. Robots like the TIAGo++ also use our know-how both in software and hardware, a knowledge that the team has been gathering from the development of cutting-edge biped humanoids like the torque-controlled TALOS.

From a technical point of view, TIAGo++ was made very compact to suit environments shared with people such as homes. Baxter was a very nice entry-point platform and was not originally designed to be a mobile manipulator but a fixed one. TIAGo++ can use the same navigation used in our commercial autonomous mobile robot for intralogistics tasks, the TIAGo Base.

Besides, TIAGo++ is a fully customizable robot in all aspects: You can select the options you want in hardware and software, so you get the ideal platform you want to have in your robotics lab. For a mobile manipulator with two 7-DoF arms, force/torque sensors, ROS-based, affordable, and with community support, we believe TIAGo++ should be a very good option.

The TIAGo community is growing around the world, and we are sure that we will see more and more robots helping people in different scenarios very soon.

What’s the price point for TIAGo++?

Pagès: The starting price is around €90,000 [$100,370 U.S.]. It really depends on the configuration, devices, computer power, sensors, and extras that each client can choose for their TIAGo robot, so the price can vary.

The post TIAGo++ robot from PAL Robotics ready for two-armed tasks appeared first on The Robot Report.

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COAST Autonomous to deploy first self-driving vehicles at rail yard

PASADENA, Calif. — COAST Autonomous today announced that Harbor Rail Services of California has selected it to deploy self-driving vehicles at the Kinney County Railport in Texas.

This groundbreaking collaboration is the first deployment of self-driving vehicles at a U.S. rail yard, said the companies. Harbor Rail and COAST teams have identified a number of areas where autonomous vehicles can add value, including staff transportation, delivery of supplies and equipment, perimeter security, and lawn mowing.

COAST Autonomous is a software and technology company focused on delivering autonomous vehicle (AV) solutions at appropriate speeds for urban and campus environments. COAST said its mission is to build community by connecting people with mobility solutions that put pedestrians first and give cities back to people.

COAST has developed a full stack of AV software that includes mapping and localization, robotics and artificial intelligence, fleet management and supervision systems. Partnering with proven manufacturers, COAST said it can provide a variety of vehicles equipped with its software to offer Mobility-as-a-Service (MaaS) to cities, theme parks, campuses, airports, and other urban environments.

The company said its team has experience and expertise in all aspects of implementing and operating AV fleets while prioritizing safety and the user experience. Last year, the company conducted a demonstration in New York’s Times Square.

Harbor Rail operates railcar repair facilities across the U.S., including the Kinney County Railport (KCRP), a state-of-the-art railcar repair facility that Harbor Rail operates near the U.S.-Mexico border. KCRP is located on 470 acres of property owned by Union Pacific, the largest railroad in North America. The facility prepares railcars to meet food-grade guidelines, so they are ready to be loaded with packaged beer in Mexico and return to the U.S. with product for distribution.

COAST completes mapping, ready to begin service

COAST has completed 3D mapping of the facility, a first step in any such deployment, and the first self-driving vehicle is expected to begin service at KCRP next month.

“Through the introduction of re-designed trucks, innovative process improvements and adoption of data-driven KPIs [key performance indicators], Harbor Rail successfully reduced railcar rejections rates from 30% to 0.03% in KCRP’s first year of operations,” said Mark Myronowicz, president of Harbor Rail. “However, I am always looking for ways to improve our performance and provide an even better service for our customers.”

COAST Autonomous to deploy first self-driving vehicles at rail yard

Source: COAST Autonomous

“At a large facility like KCRP, we have many functions that I am convinced can be carried out by COAST vehicles,” Myronowicz said. “This will free up additional labor to work on railcars, make us even more efficient, help keep the facility safe at night, and even cut the grass when most of us are asleep. This is a fantastic opportunity to demonstrate Harbor Rail’s commitment to being at the forefront of innovation and customer service.”

“This is an exciting moment for COAST, and we are looking forward to working with Harbor Rail’s industry-leading team,” said David M. Hickey, chairman and CEO of COAST Autonomous. “KCRP is exactly the type of facility that will show how self-driving technology can improve efficiency and cut costs.”

“While the futuristic vision of driverless cars has grabbed most of the headlines, COAST’s team has been focused on useful mobility solutions that can actually be deployed and create tremendous value for private sites, campuses, and urban centers,” he said. “Just as railroads are often the unsung heroes of the logistics industry, COAST’s vehicles will happily go about their jobs unnoticed and quietly change the world.”

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6 common mistakes when setting up safety laser scanners





Having worked in industrial automation for most of my career, I’d like to think that I’ve built up a wealth of experience in the field of industrial safety sensors. Familiar with safety laser scanners for over a decade, I have been involved many designs and installations.


I currently work for SICK (UK) Ltd., which invented the safety laser scanner, and I continually see people making the same mistakes time and time again. This short piece highlights, in my opinion, the most common of them.


1. Installation and mounting: Thinking about safety last


If you are going to remember just one point, then this is it. Too many times have I been present at an “almost finished” machine and asked, “Right, where can I stick this scanner?”


Inevitably, what ends up happening is that blind spots (shadows created by obstacles) become apparent all over the place. This requires mechanical “bodges” and maybe even additional scanners to cover the complete area when one scanner may have been sufficient if the cell was designed properly in the first place.


In safety, designing something out is by far the most cost-effective and robust solution. If you know you are going to be using a safety laser scanner, then design it in from the beginning — it could save you a world of pain. Consider blind zones, coverage and the location of hazards.


This also goes for automated guided vehicles (AGVs). For example, the most appropriate position to completely cover an AGV is to have two scanners adjacent to each other on the corners integrated into the vehicle (See Figure 1).


Figure 1: Typical AGV scanner mounting and integration. | Credit: SICK


2. Incorrect multiple sampling values configured


An often misunderstood concept, multiple sampling indicates how often an object has to be scanned in succession before a safety laser scanner reacts. By default and out of the box, this value is usually x2 scans, which is the minimum value. However, this value may range from manufacturer to manufacturer. A higher multiple sampling value reduces the possibility that insects, weld sparks, weather (for outdoor scanners) or other particles cause the machine to shut down.


Increasing the multiple sampling can make it possible to increase a machine’s availability, but it can also have negative effects on the application. Increasing the number of samples is basically adding an OFF-Delay to the system, meaning that your protective field may need to be bigger due to the increase in the total response time.


If a scanner has a robust detection algorithm, then you shouldn’t have to increase this value too much but when this value is changed you could be creating a hazard due to lack of effectiveness of the protective device.


If the value is changed, you should make a note of the safety laser scanner’s new response time and adjust the minimum distance from the hazardous point accordingly to ensure it remains safe.


Furthermore, in vertical applications, if the multiple sampling is set too high, then it may be possible for a person to pass through the protective field without being detected — so care must be taken. For one our latest safety laser scanners, the microScan3, we provide the following advice:


Figure 2: Recommended multiple sampling values. | Credit: SICK


3. Incorrect selection of safety laser scanner


The maximum protective field that a scanner can facilitate is an important feature, but this value alone should not be a deciding factor on whether the scanner is suitable for an application. A safety laser scanner is a Type 3 device, according to IEC 61496, and an Active Opto-Electric Protective Devices responsive to Diffuse Reflection (AOPDDR). This means that it depends on diffuse reflections off of objects. Therefore, to achieve longer ranges, scanners must be more sensitive. In reality, this means that sometimes scanning angle but certainly detection robustness can be sacrificed.


This could lead to a requirement for an increasing number multiple samples and maybe lack of angular resolution. The increased response times and lack of angle could mean that larger protective fields are required and even additional scanners — even though you bought the longer range one. A protective field should be as large as required but as small as possible.


A shorter-range scanner may be more robust than its longer-range big brother and, hence, keep the response time down, reduce the footprint, reduce cost and eliminate annoying false trips.


4. Incorrect resolution selected


The harmonized standard EN ISO 13855 can be used for the positioning of safeguards with respect to the approach speeds of the human body. Persons or parts of the body to be protected may not be recognized or recognized in time if the positioning or configuration is incorrect. The safety laser scanner should be mounted so that crawling beneath, climbing over and standing behind the protective fields is not possible.


If crawling under could create a hazardous situation, then the safety laser scanner should not be mounted any higher than 300 mm. At this height, a resolution of up 70 mm can be selected to ensure that it is possible to detect a human leg. However, it is sometimes not possible to mount the safety laser scanner at this height. If mounted below 300 mm, then a resolution of 50 mm should be used.


It is a very common mistake to mount the scanner lower than 300 mm and leave the resolution on 70mm. Reducing the resolution may also reduce the maximum protective field possible on a safety laser scanner so it is important to check.


5. Ambient/environmental conditions were not considered


Sometimes safety laser scanners just aren’t suitable in an application. Coming from someone who sells and supports these devices, that is a difficult thing to say. However, scanners are electro-sensitive protective equipment and infrared light can be a tricky thing to work with. Scanners have become very robust devices over the last decade with increasingly complex detection techniques (SafeHDDM by SICK) and there are even safety laser scanners certified to work outdoors (outdoorScan3 by SICK).


However, there is a big difference between safety and availability and expectations need to be realistic right from the beginning. A scanner might not maintain 100% machine availability if there is heavy dust, thick steam, excessive wood chippings, or even dandelions constantly in front of the field of view. Even though the scanner will continue to be safe and react to such situations, trips due to ambient conditions may not be acceptable to a user.


For extreme environments, the following question should be asked: “What happens when the scanner is not available due to extreme conditions?” This can be especially true in outdoor application in heavy rain, snow or fog. A full assessment of the ambient conditions and even potentially proof tests should be carried out. This particular issue can become a very difficult, and sometimes impossible, and expensive thing to fix.


6. Non-safe switching of field sets


A field set in a safety laser scanner can consist of multiple different field types. For example, a field set could consist of 4 safe protection fields (Field Set 1) or it could consist of 1 safe protective field, two non-safe warning fields and a safe detection field (Field set 2). See Figure 3.


Figure 3: Safety laser scanner field sets. | Credit: SICK


A scanner can store lots of different fields that can be selected using either hardwired inputs or safe networked inputs (CIP Safety, PROFISAFE, EFI Pro). This is a feature that industry finds very useful for both safety and productivity in Industry 4.0 applications.


However, the safety function (as per EN ISO 13849/EN 62061) for selecting the field set at any particular point in time should normally have the same safety robustness (PL/SIL) as the scanner itself. A safety laser scanner can be used in safety functions up to PLd/SIL2.


If we look at AGVs, for example, usually two rotary encoders are used to switch between fields achieving field switching up to PLe/SIL3. There are now also safety rated rotary encoders that can be used alone to achieve field switching to PLd/SIL2.


However, sometimes the safety of the mode selection is overlooked. For example, if a standard PLC or a single channel limit switch is used for selecting a field set, then this would reduce the PL/SIL of the whole system to possibly PLc or even PLa. An incorrect selection of field set could mean that an AGV is operating with small protective field in combination with a high speed and hence long stopping time, creating a hazardous situation.


Summary


Scanners are complex devices and have been around for a long time with lots of choice in the market with regards to range, connectivity, size and robustness. There are also a lot of variables to consider when designing a safety solution using scanners. If you are new to this technology then it is a good idea to contact the manufacturer for advice on the application of these devices.


Here at SICK we offer complimentary services to our customers such as consultancy, on-site engineering assistance, risk assessment, safety concept and safety verification of electrosensitive protective equipment (ESPEs). We are always happy to answer any questions. If you’d like to get in touch then please do not hesitate.




About the Author


Dr. Martin Kidman is a Functional Safety Engineer and Product Specialist, Machinery Safety at SICK (UK) Ltd. He received his Ph.D. at the University of Liverpool in 2010 and has been involved in industrial automation since 2006 working for various manufacturers of sensors.


Kidman has been at SICK since January 2013 as a product specialist for machinery safety providing services, support and consultancy for industrial safety applications. He is a certified FS Engineer (TUV Rheinland, #13017/16) and regularly delivers seminars and training courses covering functional safety topics. Kidman has also worked for a notified body testing to the Low Voltage Directive in the past.


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MiR500 mobile robot helps Cabka automate pallet transport
	


	
	

		








Germany-based Cabka Group recycles post-industrial plastics into pallets and other material handling products. Cabka North America’ 400,000-square-foot plant in the St. Louis, Missouri area runs 24/7 to manufacture about 5,000 pallets per day.


But Cabka is challenged by labor shortages due to high turnover of temporary workers, which leads to expensive downtime. At Cabka North America’s facility, workers at eleven injection molding machines unload plastic pallets and manually trim and stack them for material handlers to transport to the warehouse using fork trucks or pallet jacks. The work is repetitive and physical, making it hard to retain workers, and the presence of fork trucks on the production floor leads to safety concerns.


However, a new, fully automated production line that will be replicated throughout the facility is helping minimize dependency on temporary workers while also improving product quality and worker safety.


A Mobile Industrial Robots MiR500 autonomous mobile robot is part of that fully automated production line. The production line also includes a Krauss Maffei six-axis robot to autonomously unload pallets from the injection molding machine, trim the pallets, and load the finished products directly onto the MiR500. The MiR500, which is equipped with a MiR pallet lift, transports the finished products out of the manufacturing floor to a separate staging area as soon as the job is complete.


In the staging area, the pallets can be checked for quality and wrapped. Fork trucks then transport the finished pallets to the warehouse and loading docks without having manufacturing workers present. This will allow Cabka to eliminate fork truck traffic in the production area, replacing them with safe, collaborative mobile robots.


MiR500
Cabka North America uses a MiR500 autonomous mobile robot to transport plastic pallets. | Credit: Mobile Industrial Robots


Pilot project leads to fully optimized production


The fully automated production line is intended to be the model for the eventual automation of all eleven production lines, with a fleet of MiR robots supporting them in a dynamic, highly efficient manufacturing floor. Each AMR can go where it’s needed when it’s needed to keep production flowing.


Cabka estimates the first MiR500 travels about three miles a day supporting one production line. With eleven lines planned for autonomous material transport with multiple MiR robots, workers and fork truck drivers will be relieved from many miles of manual material handling, allowing Cabka to redeploy those workers to higher-value tasks.


“With the MiR500, we are very happy with the payload,” said Cabka project technician Craig Bossler. “It’s handled everything that we can stack on top of it. We haven’t found out how high we can go yet. It’s very stable — it can make turns, go straight, and it can hit bumps, and it’s always very stable. The MiR definitely can handle all the imperfections in the floor.”


MiR500
Production of MiR5000 autonomous mobile robots. The company says 40 percent of its sales has gone to the U.S. | Credit: Mobile Industrial Robots


Adding more MiR500 mobile robots


Cabka North America is looking at other ways to use the MiR robots, including prepping orders overnight in the warehouse so they will be ready at the dock for loading in the morning. Patrick Garin, president of Cabka North America, anticipates that other Cabka locations will be following the North American facility’s lead.


“We always have our corporate people come here – our corporate CEO and the other part of the team – and they will definitely be very interested in seeing our progress here,” he said.


Teradyne Inc. of North Reading, Mass., recently acquired Mobile Industrial Robots of Odense, Denmark. Three years ago, Teradyne also purchased another Danish automation company, collaborative robot maker Universal Robots.


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Brain Corp Europe opens in Amsterdam
	


	
	

		


A BrainOS-powered autonomous floor scrubber. | Credit: Brain Corp


San Diego-based Brain Corp, the Softbank-backed developer of autonomous navigation systems, has opened its European headquarters in Amsterdam. The reason for the expansion is two-fold: it helps Brain better support partners who do business in Europe, and it helps Brain find additional engineering talent.


“Amsterdam is a fantastic gateway to Europe and has one of the largest airports in Europe,” Sandy Agnos, Brain’s Director of Global Business Development, told The Robot Report. “It’s very business and tech friendly. It is the second-fastest-growing tech community, talent-wise, in Europe.”


Brain hired Michel Spruijt to lead Brain Corp Europe. He will be tasked with driving sales of BrainOS-powered machines, providing partner support, and overseeing general operations throughout Europe. Agnos said Brain was impressed by Spruijt’s previous experience growing an office from “a few employees to over 100 was impressive to us.”


“Under Michel Spruijt’s guidance, our vision of a world where the lives of people are made safer, easier, more productive, and more fulfilling with the help of robots will extend into Europe,” said Eugene Izhikevich, Brain Corp’s Co-Founder and CEO.


Agnos said there will initially be about 12 employees at Brain Corp Europe who focus mostly on service and support. She added that Brain is recruiting software engineering talent and will continue to grow the Amsterdam office.


A rendering of how BrainOS-powered machines sense their environment. | Credit: Brain Corp


Brain planning worldwide expansion


The European headquarters marks the second international office in Brain’s global expansion. The company opened an office in Tokyo in 2017. This made sense for a couple of reasons. Japanese tech giant Softbank led Brain’s $114 million funding round in mid-2017 via the Softbank Vision Fund. And Softbank’s new autonomous floor cleaning robot, Whiz, uses Brain’s autonomous navigation stack.


Agnos said Brain is planning to add other regional offices after Amsterdam. The dates are in flux, but future expansion includes:


    

  • Further growth in Europe in 2020
    • 

  • Expansion in Asia Pacific, specifically Australia and Korea, in mid- to late-2020
    • 

  • South America afterwards
    • 



“We follow our partners’ needs,” said Agnos. “We are becoming a global company with support offices around the world. The hardest part is we can’t expand fast enough. Our OEM partners already have large, global customer bases. We need to have the right people and infrastructure in each location.”








BrainOS-powered robots


BrainOS, the company’s cloud-connected operating system, currently powers thousands of floor care robots across numerous environments. Brain recently partnered with Nilfisk, a Copenhagen, Denmark-based cleaning solutions provider that has been around for 110-plus years. Nilfisk is licensing the BrainOS platform for the production, deployment, and support of its robotic floor cleaners.


Walmart, the world’s largest retailer, has 360 BrainOS-powered machines cleaning its stores across the United States. A human needs to initially teach the BrainOS-powered machines the layout of the stores. But after that initial demo, BrainOS’ combination of off-the-shelf hardware, sensors, and software enable the floor scrubbers to navigate autonomously. Brain employs a collection of cameras, sensors and LiDAR to ensure safety and obstacle avoidance. All the robots are connected to a cloud-based reporting system that allows them to be monitored and managed.


At ProMat 2019, Brain debuted AutoDelivery, a proof-of-concept autonomous delivery robot designed for retail stores, warehouses, and factories. AutoDelivery, which can tow several cart types, boasts cameras, 4G LTE connectivity, and routing algorithms that allow it to learn its way around a store. AutoDelivery isn’t slated for commercial launch until early 2020.


Izhikevich recently told The Robot Report that Brain is exploring other types of mobile applications, including delivery, eldercare, security and more. In July 2018, Brain led a $13.4 million Series B for Savioke, which makes autonomous delivery robots. For years, Savioke built its autonomous navigation stack from scratch using ROS.
	


	





		

		
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Stanford Doggo robot acrobatically traverses tough terrain
	


	
	

		


Putting their own twist on robots that amble through complicated landscapes, the Stanford Student Robotics club’s Extreme Mobility team at Stanford University has developed a four-legged robot that is not only capable of performing acrobatic tricks and traversing challenging terrain, but is also designed with reproducibility in mind. Anyone who wants their own version of the robot, dubbed Stanford Doggo, can consult comprehensive plans, code and a supply list that the students have made freely available online.


“We had seen these other quadruped robots used in research, but they weren’t something that you could bring into your own lab and use for your own projects,” said Nathan Kau, ’20, a mechanical engineering major and lead for Extreme Mobility. “We wanted Stanford Doggo to be this open source robot that you could build yourself on a relatively small budget.”


Whereas other similar robots can cost tens or hundreds of thousands of dollars and require customized parts, the Extreme Mobility students estimate the cost of Stanford Doggo at less than $3,000 — including manufacturing and shipping costs. Nearly all the components can be bought as-is online. The Stanford students said they hope the accessibility of these resources inspires a community of Stanford Doggo makers and researchers who develop innovative and meaningful spinoffs from their work.


Stanford Doggo can already walk, trot, dance, hop, jump, and perform the occasional backflip. The students are working on a larger version of their creation — which is currently about the size of a beagle — but they will take a short break to present Stanford Doggo at the International Conference on Robotics and Automation (ICRA) on May 21 in Montreal.


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A hop, a jump and a backflip


In order to make Stanford Doggo replicable, the students built it from scratch. This meant spending a lot of time researching easily attainable supplies and testing each part as they made it, without relying on simulations.


“It’s been about two years since we first had the idea to make a quadruped. We’ve definitely made several prototypes before we actually started working on this iteration of the dog,” said Natalie Ferrante, Class of 2019, a mechanical engineering co-terminal student and Extreme Mobility Team member. “It was very exciting the first time we got him to walk.”


Stanford Doggo’s first steps were admittedly toddling, but now the robot can maintain a consistent gait and desired trajectory, even as it encounters different terrains. It does this with the help of motors that sense external forces on the robot and determine how much force and torque each leg should apply in response. These motors recompute at 8,000 times a second and are essential to the robot’s signature dance: a bouncy boogie that hides the fact that it has no springs.


Instead, the motors act like a system of virtual springs, smoothly but perkily rebounding the robot into proper form whenever they sense it’s out of position.


Among the skills and tricks the team added to the robot’s repertoire, the students were exceptionally surprised at its jumping prowess. Running Stanford Doggo through its paces one (very) early morning in the lab, the team realized it was effortlessly popping up 2 feet in the air. By pushing the limits of the robot’s software, Stanford Doggo was able to jump 3, then 3½ feet off the ground.


“This was when we realized that the robot was, in some respects, higher performing than other quadruped robots used in research, even though it was really low cost,” recalled Kau.


Since then, the students have taught Stanford Doggo to do a backflip – but always on padding to allow for rapid trial and error experimentation.


Stanford Doggo robot acrobatically traverses tough terrain
Stanford students have developed Doggo, a relatively low-cost four-legged robot that can trot, jump and flip. (Image credit: Kurt Hickman)


What will Stanford Doggo do next?


If these students have it their way, the future of Stanford Doggo in the hands of the masses.


“We’re hoping to provide a baseline system that anyone could build,” said Patrick Slade, graduate student in aeronautics and astronautics and mentor for Extreme Mobility. “Say, for example, you wanted to work on search and rescue; you could outfit it with sensors and write code on top of ours that would let it climb rock piles or excavate through caves. Or maybe it’s picking up stuff with an arm or carrying a package.”


That’s not to say they aren’t continuing their own work. Extreme Mobility is collaborating with the Robotic Exploration Lab of Zachary Manchester, assistant professor of aeronautics and astronautics at Stanford, to test new control systems on a second Stanford Doggo. The team has also finished constructing a robot twice the size of Stanford Doggo that can carry about 6 kilograms of equipment. Its name is Stanford Woofer.


Note: This article is republished from the Stanford University News Service.
	


	





		

		
发布于
The Robot Report May 2019 issue on mobile robotics
	


	
	

		




We hope you enjoy the latest edition of The Robot Report, a special print section dedicated to mobile robotics. This appeared in the May 2019 issue of Design World, our sister publication and flagship publication at WTWH Media. Here is a breakdown of the mobile robotics topics covered inside:


Robotics Summit 2019 to take a closer look at mobile robots

Mobile robot engineers and users can learn from technology and industry leaders at the Robotics Summit & Expo, which runs June 5-6 in Boston.


What Amazon’s acquisition of Canvas Technology means

Amazon’s acquisition demonstrates the importance of safe navigation for developers and users of supply chain automation.


Augmenting SLAM with deep learning

SLAM is being gradually developed towards Spatial AI, the common sense spatial reasoning that will enable robots and other devices to operate in general ways in their environments.


Mobile robot trends from Automate/ProMat

At Automate/ProMat 2019 in Chicago, robotics developers checked out the latest products for manufacturing and logistics. Here are some robotics trends we saw at the show.


Expert roundtable: mobile robotics challenges and opportunities

A3’s Jeff Burnstein chats with leading autonomous mobile robot providers about market growth, technical challenges, and opportunities.


Integrating AI with fleet management software advances AMR collaboration

Data from new sensors, in combination with AI and machine learning, is making autonomous mobile robots or AMRs more flexible and safer around humans.


How 5G will impact mobile robots

Leading robotics companies share their opinions about how 5G will impact autonomous mobile robots.


If you are interested in contributing content to an upcoming special issue of The Robot Report, please reach out to me at scrowe@wtwhmedia.com or Eugene Demaitre at edemaitre@wtwhmedia.com. If you are interested in sponsorship opportunities of upcoming special issues, please reach out to Courtney Seel at cseel@wtwhmedia.com.
	


	





		

		
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Techmetics introduces robot fleet to U.S. hotels and hospitals
	


	
	

		


Fleets of autonomous mobile robots have been growing in warehouses and the service industry. Singapore-based Techmetics has entered the U.S. market with ambitions to supply multiple markets, which it already does overseas.


The company last month launched two new lines of autonomous mobile robots. The Techi Butler is designed to serve hotel guests or hospital patients by interacting with them via a touchscreen or smartphone. It can deliver packages, room-service orders, and linens and towels.


The Techi Cart is intended to serve back-of-house services such as laundry rooms, kitchens, and housekeeping departments.


“Techmetics serves 10 different applications, including manufacturing, casinos, and small and midsize businesses,” said Mathan Muthupillai, founder and CEO of Techmetics. “We’re starting with just two in the U.S. — hospitality and healthcare.”


Building a base


Muthupillai founded Techmetics in Singapore in 2012. “We spent the first three years on research and development,” he told The Robot Report. “By the end of 2014, we started sending out solutions.”


“The R&D team didn’t just start with product development,” recalled Muthupillai. “We started with finding clients first, identified their pain points and expectations, and got feedback on what they needed.”


“A lot of other companies make a robotic base, but then they have to build a payload solution,” he said. “We started with a good robot base that we found and added our body, software layer, and interfaces. We didn’t want to build autonomous navigation from scratch.”


“Now, we’re just getting components — lasers, sensors, motors — and building everything ourselves,” he explained. “The navigation and flow-management software are created in-house. We’ve created our own proprietary software.”


“We have a range of products, all of which use 2-D SLAM [simultaneous localization and mapping], autonomous navigation, and many safety sensors,” Muthupillai added. “They come with three lasers — two vertical and one horizontal for path planning. We’re working on a 3-D-based navigation solution.”


“Our robots are based on ROS [the Robot Operating System],” said Muthupillai. “We’ve created a unique solution that comes with third-party interfaces.”


Techmetics offers multiple robot models for different industries.
Source: Techmetics


Techmetics payloads vary


The payload capacity of Techmetics’ robots depends on the application and accessories and ranges from 250 to 550 lb. (120 to 250 kg).


“The payload and software are based on the behavior patterns in an industry,” said Muthupillai. “In manufacturing or warehousing, people are used to working around robots, but in the service sector, there are new people all the time. The robot must respond to them — they may stay in its path or try to stop it.”


“When we started this company, there were few mobile robots for the manufacturing industry. They looked industrial and had relatively few safety features because they weren’t near people,” he said. “We changed the form factor for hospitality to be good-looking and safer.”


“When we talk with hotels about the Butler robots, they needed something that could go to multiple rooms,” Muthupillai explained. “Usually, staffers take two to three items in a single trip, so if a robot went to only one room and then returned, that would be a waste of time. Our robots have three compartment levels based on this feedback.”


Elevators posed a challenge for the Techi Butler and Techi Cart — not just for interoperability, but also for human-machine interaction, he said.


“Again, people working with robots didn’t share elevators with robots, but in hospitals and hotels, the robot needs to complete its job alongside people,” Muthupillai said. “After three years, we’re still modifying or adding functionalities, and the robots can take an elevator or go across to different buildings.”


“We’re not currently focusing on the supply chain industry, but we will license and launch the base into the market so that third parties can create their own solutions,” he said.


Techmetics' Techi Cart transports linens
Techi Cart transports linens and towels in a hotel or hospital. Source: Techmetics


Differentiators for Techi Butler and Cart


“We provide 10 robot models for four industries — no single company is a competitor for all our markets,” said Muthupillai. “We have three key differentiators.”


“First, customers can engage one vendor for multiple needs, and all of our robots can interact with one another,” he said. “Second, we talk with our clients and are always open to customization — for example, about compartment size — that other’s can’t do.”


“Third, we work across industries and can share our advantages across them,” Muthupillai claimed. “Since we already work with the healthcare industry, we already comply with safety and other regulations.”


“In hospitals or hotels, it’s not just about delivering a product from one point to another,” he said. “We’re adding camera and voice-recognition capabilities. If a robot sees a person who’s lost, it can help them.”


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Distribution and expansion


Techmetics’ mobile robots are manufactured in Thailand. According to Muthupillai, 80% of its robots are deployed in hotels and hospitals, and 20% are in manufacturing. The company already has distributors in Australia, Taiwan, and Thailand, and it is leveraging existing international clients for its expansion.


“We have many corporate clients in Singapore,” Muthupillai said. “The Las Vegas Sands Singapore has deployed 10 robots, and their headquarters in Las Vegas is considering deploying our products.”


“Also, U.K.-based Yotel has two hotels in Singapore, and its London branch is also interested,” he added. “The Miami Yotel is already using our robots, and soon they will be in San Francisco.”




Techmetics has three models for customers to choose from. The first is outright purchase, and the second is a two- or three-year lease. “The third model is innovative — they can try the robots from three to six months or one year and then buy,” Muthupillai said.


Muthupillai said he has moved to Techmetics’ branch office in the U.S. to manage its expansion. “We’ll be doing direct marketing in California, and we’re in the process of identifying partners, especially on the East Coast.”


“Only the theme, colors, or logos changed. No special modifications were necessary for the U.S. market,” he said. “We followed safety regulations overseas, but they were tied to U.S. regulations.”


“We will target the retail industry with a robot concierge, probably by the end of this year,” said Muthupillai. “We will eventually offer all 10 models in the U.S.”