Earlier this year, we announced support for playing back ROS 2 bags in Foxglove Studio. We were thrilled to see the community's enthusiasm for broader ROS compatibility, so in the weeks since that release, we've been working hard to expand Studio's ROS 2 support.

Today, we're excited to announce that v0.18 of Studio allows you to connect to a live ROS 2 stack with two new data source options – ROS 2 (beta) and ROS 2 Rosbridge. Whether you're running ROS on your local machine or a physical robot, you can now connect directly to your ROS 2 nodes to visualize their data in real-time.

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While we're approaching feature parity with ROS 1, our long-term vision for ROS 2 compatibility is still evolving. Beyond the preliminary support in this release, we're still working with the larger ROS community to bridge the gap between what we can achieve now and the upstream work that remains (like message definitions at runtime and in bag files).

With that said, we're excited for you to test this feature out in the field, and to give us feedback on how we can improve and expand on it. Feel free to share your thoughts in Slack, file bug reports and feature requests on GitHub, or message us directly on Twitter.

If you experience any issues with native ROS 2 connections, you can always fall back to our more battle-tested ROS 2 Rosbridge connection option. Check out our docs for more details on how to connect to all our supported data sources.


For today's spotlight, we invited Aditya Kamath, a robotics systems engineer, to talk to us about his latest project – a robot platform to help the next generation of roboticists learn ROS. As someone who’s spent years tinkering with prototyping tools, computers, and electronics, Aditya had an obvious solution for countering his lockdown boredom – building (multiple!) robots from scratch. We discuss the exciting milestones he’s reached, and his future plans to help aspiring roboticists follow in his footsteps.

Our team first stumbled upon your work when we saw you using Foxglove Studio to visualize your robots. Tell us a little bit about yourself, and how you first became interested in robotics!

I am Aditya Kamath, an Embedded / Robotics Systems Engineer based in Eindhoven, the Netherlands. I currently work as an Embedded Systems Consultant, designing embedded software for complex machines and mechatronic components. I keep my passion for robotics alive by tinkering around with robotic builds, microcontrollers / single-board computers, and rapid prototyping tools like 3D printing.

Aditya Kamath

I earned my Bachelor’s in Electronics and Communication Engineering from MIT Manipal in India (2014). Then, I received a Master of Science (MSc) in Systems and Control and a Professional Doctorate in Engineering (PDEng) in Mechatronic Systems Design from TU Eindhoven (2019). Despite studying many different things, the common denominator in my education and extracurricular experiences has always been the field of autonomous robotics.

What exciting robotics projects are you working on now?

With all my spare time during the COVID-19 lockdown last year, I decided that I wanted to build some robots to experiment with ROS. I also saw this as an opportunity to learn more about 3D SLAM and depth and point cloud processing. The first several months, I focused on building a few Jetson Nano-based ROS robots using some rapid prototyping tools. For one, I used the NVidia JetRacer, an autonomous AI racecar with Ackermann steering, with custom add-ons. For another, I used the NVidia JetBot, an open source robot with differential drive geared towards educational purposes, again with custom add-ons.

Then at the start of this year, I was able to get a LIDAR and an OAK—D camera. With these exciting new supplies, I decided to use everything I had learned the previous months to design and implement my own ROS 1 robot platform from scratch. I named the project AKROS, a working name that combines my initials and ROS – for until I come up with something more original.

robot with LIDAR and camera
The robot with the new LIDAR and OAK—D camera attached.

All the software for AKROS (ROS Noetic) runs on a Raspberry Pi 4. It has a mobile base with omni wheels and four-wheel drive, with each wheel powered by a motor that computes the robot's odometry using encoders. The mounted RPLIDAR A2 provides a 2D laser scan, while the OAK—D camera provides RGB images, stereo depth images, and spatial object detection outputs using the on-board DepthAI module. The Intel Realsense T265 tracking camera provides simultaneous localization and mapping.

What development tools do you use for iterating on AKROS?

I do all my development using JupyterLab – the server runs on the Raspberry Pi, and I open my workspace from any browser on the network. However, this method limits you to the terminal, so for tools like RViz, I have to install and configure ROS on my Windows laptop. After that, I still have to go through three to four additional steps to launch RViz, which unfortunately cannot run directly on Windows. On top of all this, it's easy to forget setting the necessary environment variables to connect to the remote ROS master. The whole process is very annoying and manual.

Once I started playing around with Foxglove Studio, I thought it was a really convenient way to visualize ROS topics and messages from a remote desktop. I love that it works on Windows, because that means I don’t have to go through the process of launching ROS from Windows, setting environment variables, and finally launching RViz. Foxglove takes care of all this for me!

A demo of AKROS's SLAM and object detection capabilities, visualized in Foxglove Studio.

Using Studio on Windows is as easy as using Rviz on a Ubuntu laptop. Now, I can run my ROS launch files from the JupterLab terminal in my browser, then open up Foxglove Studio to start visualizing everything I want – no more complex setup process.

We're so glad to see that Studio has been able to streamline your development process. What do you have planned next on your roadmap?

While this robot fulfills my personal learning goals, I want to take AKROS and develop it into a product that could be used to teach robotics or to perform research in applications like control systems, computer vision, and AI. In fact, I am currently in talks with university students and professors to understand their requirements for a ROS robot platform. Eventually, I want to design a polished product for these end-users, instead of a hacky prototype for just myself.

At this point of time, I am still in the development process. I have two main short-term goals – to set up the ROS navigation stack with the RPLIDAR’s laser scans and Intel Realsense tracking camera’s odometry, and to set up 3D mapping with the OAK-D camera. It's been an iterative process – I recently had to completely redesign my navigation module to accommodate my tracking camera.

unmounted and mounted navigation module
Aditya spent quite some time iterating on his navigation module - adding components, fine-tuning its assembly, redesigning the frame - before mounting it on the rest of his robot.

Do you have any advice for someone who's interested in getting into robotics, either as a hobbyist or startup founder?

The best experience you can get is by building your own robot –  it’s also much more fun than doing an online course or working with a simulation. There are lots of (free and open source) resources out there that will teach you the fundamentals step by step, and cheap robot kits are abundant online. By building your own physical robot, you learn a lot more about robotics than just how to program.

To keep up with Aditya's latest work, check out his project updates on his Twitter, Instagram, and blog.

If you're a university professor or student interested in collaborating with Aditya for his AKROS project, you can get in touch with him directly on Twitter.

This interview has been edited and condensed for clarity.


As an embedded software engineer at the Woods Hole Oceanographic Institution (WHOI), Ryan Govostes helps researchers across the institution on R\&D projects capture and interpret scientific data. He stumbled upon Foxglove Studio earlier this year in his quest for flexible visualizations, and has been using the tool ever since to accelerate development for his teammates – whether that’s by building them custom tools or surfacing meaningful patterns in complex data. We discuss the exciting projects he’s contributed to, and what lies on the horizon for him.

Tell us a little bit about yourself! How did you first become interested in robotics?

My background is actually in information security and has nothing to do with robotics. I spent the first part of my career in Silicon Valley, focusing on developing technologies to defend software against hackers.

A few years ago, I visited the Computer History Museum to attend a symposium on the Antikythera Mechanism, this amazing ancient analog computer that was discovered on a shipwreck in the Aegean Sea. One of the presenters was Brendan Foley, an archaeologist then at WHOI, who was involved in a new survey of the shipwreck. His team was using underwater robots to search for artifacts missed by Jacques Cousteau decades earlier. I just thought it was the coolest thing I’d ever heard of.

What really stuck with me from this presentation was that Brendan estimates there are 750,000 ancient shipwrecks sitting at the bottom of the Mediterranean – the number we’ve found is a minute fraction of that. I joined WHOI a few years later, hoping to develop technologies for making the next discoveries at scale.

What do you find compelling about leveraging robots specifically for ocean exploration?

I’d never really thought about how little of the ocean we have explored below the surface. There are so many constraints with human exploration – like how do you safely investigate what’s happening to the ocean during a hurricane? Or monitor a site over years to understand the effects of climate change?

Robots have plenty of their own challenges, but they have amazing capabilities. For example, we have gliders that can collect and transmit data back to shore via satellite for six months at a time. They are completely game-changing for our understanding of the ocean.

Remus 6000

The REMUS 6000 can go to depths of 6,000 meters and spend nearly a full day exploring. (© Woods Hole Oceanographic Institution, M. Purcell)

What do you find especially exciting about your work? How would you characterize its impact?

It’s exciting to be building technologies for exploring new frontiers. The upgraded HOV Alvin will allow scientists to study 98% of the ocean floor in person.Some researchers are even thinking about using robots to explore oceans in other worlds, like Jupiter’s moon Europa.

HOV Alvin

The HOV Alvin will be going out for sea trials at depths of 6,500m later this year. (© Woods Hole Oceanographic Institution, L. Lamar)

There’s an incredible urgency to understanding how a warming ocean will affect life on Earth, both above and below the surface. We are in the first year of the United Nations Decade of Ocean Science for Sustainable Development, a concerted effort among scientists, policy makers, and consumers to ensure the preservation of our oceans for future generations. It’s an especially important time for software engineers to contribute to ocean science – to data pipelines, automation, machine learning, and so on.

What does a typical day for you look like? What projects are you working on now, and what are some of the interesting development challenges you’ve encountered?

There’s something new to learn every day. Since I lend programming expertise to researchers across the Institution, I might be collaborating with a biologist to monitor for harmful algal blooms one week, then calibrating a camera system for an underwater vehicle the next. I’ve mostly gotten over my reluctance to ask incredibly basic questions – the other day I asked why an autonomous underwater vehicle (AUV) was so heavy, forgetting that underwater vehicles aren’t supposed to float.

Most recently, I’ve been working with a team on a new propulsion technology called Asymmetric Propulsion. Traditionally, an AUV has a propeller to generate thrust and some other mechanism like fins to control steering. But by varying the velocity of the propeller over the course of a rotation, my collaborators realized they could generate thrust and steer with a single propeller blade – similar to how you can steer a kayak by paddling harder to one side. This enables vehicles that are more maneuverable and reliable, with fewer points of failure.

Asymmetric Propulsion

An AUV executing a turn to port with a single propeller blade, using Asymmetric Propulsion. (© Woods Hole Oceanographic Institution, J. Kaeli, R. Littlefield, F. Jaffre)

This was my first major robotics project – and one of my first times using ROS – so there were plenty of challenges. In ROS, I think there’s an illusion that it’s easy to develop a robot, because you can choose from a large number of available packages and just glue components together. In reality, I needed to spend time becoming familiar with each package and understanding the benefits or drawbacks it could introduce to the finished system.

Meanwhile, my collaborators were eager to test and study the propulsion system. I had to be very strategic about the order in which I wrote the code, so I didn’t disrupt their work. One of the first things I did was jury-rig a tool using the web browser Gamepad API, plus a couple of socat processes to relay commands to the motor controller over Wi-Fi. It allowed my teammates to drive the vehicle around on a test tank, while I developed target-tracking capabilities. To learn more about this whole software development process, you can check out our talk for the OCEANS 2021 conference this week.

motor controller
The superimposed red line above shows the vehicle's position over time, as researchers navigate it around a test tank. (© Woods Hole Oceanographic Institution, R. Govostes)

It seems like you support a pretty wide range of workflows for different teams across the institution. What kind of tooling do you use when developing solutions for these various workflows?

There’s a terrific talk by Bret Victor called “Media For Thinking the Unthinkable”, where he argues that the representation of a complex system is how we think about that system – to build powerful new systems, we need powerful new representations. With the appropriate visualizations, you can recognize patterns and understand underlying relationships that reveal more about the larger system.

This is what really excited me about using Foxglove Studio to help our team understand Asymmetric Propulsion, where we have this non-obvious relationship between the propeller’s angular velocity and the AUV’s steering behavior. Everyone on the team comes from a different discipline and has different areas of expertise. We have a brilliant mechanical engineer who designed this AUV and has gotten its buoyancy and trim perfectly dialed in, but it’s not his job to know arcane ROS command line invocations or to write code to plot gyroscope data. Having an intuitive, flexible tool in Foxglove Studio has really empowered him and the rest of the team.

I also love that Studio is open source and allows us to write custom panels specific to our project. There are so many excellent JavaScript visualization libraries out there, like D3.js – having an extension API lets me leverage any of these tools to accomplish my task. I recently hosted a workshop at WHOI’s new innovation accelerator for Autonomous Vehicles and Sensor Technologies (AVAST), where we took an example polar plot and turned it into a Studio extension showing live ROS data in under an hour.

What do you have planned next?

I’m really excited about supporting the Scibotics Lab at WHOI with developing a long-range autonomous underwater vehicle (LRAUV) for under-ice oil spill detection and mapping, in collaboration with the Monterey Bay Aquarium Research Institute (MBARI) and the Arctic Domain Awareness Center. The goal is to be able to quickly deploy the LRAUV at the site of an environmental disaster to survey and help mitigate its impact.

LRAUV

The LRAUV can be deployed from a helicopter to provide first responders with crucial situational awareness to manage an environmental crisis. (© Woods Hole Oceanographic Institution, S. P. Whelan)

The vehicle is a remarkable piece of engineering that has tremendous potential in enabling new scientific missions. It combines elements of traditional AUV propulsion with the greater endurance of gliders. We’ve started integrating ROS on the vehicle, so we can share software capabilities across the Institution’s heterogeneous fleet of autonomous vehicles.

What advice would you share to someone who's interested in getting into robotics, either as a hobbyist or a professional contributor like yourself?

I admittedly took a pretty unusual path into robotics, and believe there is a lot of value in being multidisciplinary and drawing inspiration from other fields, even if they seem superficially unrelated.

One of my favorite examples of this comes from an incredible team at WHOI called the WARPLab that is using topic modeling techniques to inform exploration. Topic modeling is typically associated with natural language processing – it’s often used to categorize bodies of text by subject matter without explicitly knowing the subjects ahead of time.

This team is applying this idea to camera images, so their AUV can differentiate patches of seagrass from, say, a sandy region it saw a moment ago. As such, it can recognize when it has encountered something novel and decide to investigate.

This is all to say that you may be surprised how often what you already know translates to a new field. It’s very possible you have already developed skills that could be usefully applied to robotics.

Hero image © Woods Hole Oceanographic Institution, R. Govostes


Spotlight: Ryan Govostes on Exploring a New Frontier with Foxglove Studio

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