If you’ve opened Foxglove Studio recently, you’ll notice that you’re now greeted by a dialog that prompts you to "Get started". It provides a list of live and recorded data sources you can visualize, alongside helpful resources you can reference.

Before this dialog was added, new Studio users often struggled to start seeing any meaningful visualizations in the app. There was no clear indication of the steps they had to take, in which order, to get to a useful view. Even veteran users who'd figured out what to do had to click multiple times through a long list of options to get up and running.

before the dialog

In response to this confusing workflow, we designed this new hard-to-miss Data source dialog to make it easier than ever to load your data in Foxglove Studio. In addition to seeing the dialog on app load, you can also open it from the sidebar's Data source tab whenever you want to pull in a new data source.

Load a data source

The redesigned Data source dialog makes it extremely easy to understand the types of data Foxglove Studio supports – from local and remote files (in a variety of formats), to live connections for different frameworks and hardware. The dialog also has an option for you to explore some sample self-driving data, to get a sense of how Foxglove Studio can help you explore and analyze robotics data. This is a great way to get started, especially if you don't have your own robotics data on hand, or just want inspiration for how you can compose Studio layouts to best investigate your data.

sample data

Drill down into one of these data source options to see more detailed configuration options. For example, clicking into “Open connection” will prompt you for different information depending on whether you're connecting live to a live ROS stack, a custom data stream, or some Velodyne LIDAR hardware.

connection details

Reconnect to a data source

The dialog's Recents section makes it easy to revisit a particular data source.

recents section

This is especially helpful, if you know you'll be calibrating your LIDAR sensor, teleoperating your ROS robot, or loading a particular log file repeatedly. Instead of having to select a file, paste a URL, or configure a connection over and over again, you can jump right back into a data source with a single click.

Get help with connecting

Finally, the dialog's Help section provides a list of links you can use if you find yourself stuck on connecting to your data source. Join our Slack community for live support, read the Studio docs for troubleshooting tips, or file a GitHub issue for larger requests.

help section

We hope this streamlined workflow helps both our newcomers and power users alike connect to their robotics data more easily. As always, please feel free to reach out to us directly if you have any feedback or questions. To follow along with our ongoing development, subscribe to our newsletter and check out our updates on Twitter.


Robot kits are a great way to learn the basics of robotics development, because you can leverage pre-built platforms to focus on the field's most exciting problems. There are several companies that curate, assemble, and provide these kits. Yahboom, for example, sells a range of educational robot kits for everyone from the casual hobbyist to professional researcher. After recently trying out their Transbot platform, I can say that I'm a big fan. Based on how easy it was to get up and running, I would recommend it to anyone interested in ditching the textbooks and getting their hands dirty with some hands-on development.

Assembling the Transbot

I ordered the Transbot kit with a Jetson NANO, HD camera, and Depth (LIDAR) camera. My Transbot and its accompanying sensors and accessories arrived in a conveniently insulated carrying case, along with a microSD card pre-installed with ROS.

Transbot case
Here I’ve taken out all the accessories to reveal the securely packed Transbot at the bottom of the shipped case.

First, I unpacked all the various accessories – a wireless controller with alkaline batteries included, a camera calibration card, the Jetson NANO, and more. The kit also includes a rechargeable battery for the bot, as well as an expansion board with all the motor and servo controllers.

Transbot accessories

I really appreciated that the bot comes 90% assembled – this lets you get started with the platform without struggling through complex assembly instructions. For the rest, the instruction manual (Chinese and English) was relatively easy to understand, especially for a kit of this complexity. I was able to assemble the entire bot within an hour – this involved mounting the camera and LIDAR assembly, the expansion board, and Jetson NANO on top of the base.

assembled Transbot
The Transbot base as shipped vs. after assembly.

Connecting your Transbot to Foxglove Studio

After assembling the physical hardware components, I realized that I needed software to help me understand what my robot was seeing and doing. I decided to connect my Transbot to Foxglove Studio, a cross-platform robotics visualization tool compatible with many robotics platforms, to inspect and debug my robot as I went.

By default, the Transbot sets up a Wi-Fi network. By connecting my laptop to this same network ("Transbot"), I am ready to talk directly to my robot's ROS system and inspect it with Foxglove Studio.

connecting to Transbot

Download the Studio desktop app – use the dialog that appears on app open to open a new ROS 1 connection (Open connection → ROS 1):

Studio's data source dialog

The ROS\_MASTER\_URI should be set to your Transbot's IP address. The ROS\_HOSTNAME should be set to your laptop's IP address on the "Transbot" WiFi network – this is how your bot's ROS nodes will send data to Studio on your laptop.

Transbot's OLED screen
Check your Transbot's OLED screen for its IP address.

You’re now ready to start visualizing your robot's data!

Visualizing your Transbot’s data in Foxglove Studio

In Foxglove Studio, let’s create a layout of panels that we'll use to visualize data our bot data. Open the Layouts menu from the app's sidebar, and add a new layout.

Next, let's add a 3D panel to this newly created layout to visualize the Transbot's LIDAR data, which the Depth camera collects via a 360° scan around the robot. Open the Add panel menu, also from the app's sidebar, to see a list of all available panels.

grid of panels in Studio

Once we’ve selected the 3D panel, let's toggle on the /scan topic in the topic picker. Let's also update the orientation controls on the right (base\_link → laser), so we can view the LIDAR data from the POV of the sensor.

We now see the LIDAR from our robot! The raw scan details match the room my Transbot is in – I can see outlines of the walls, door, and random boxes, as well as the areas that the sensor isn't able to "see".

zoomed in view of 3D panel

Before we drive the robot around with the included wireless controller, let’s set up some charts to plot the controller's velocity commands. Again, using the Add panel menu, add a Plot and Raw Messages panel. The Plot panel will show me the history of values, while the Raw Messages panel will display the current value, for a given message path. In the Plot panel, let's plot /cmd\_vel.linear.x and /cmd\_vel.angular.z over time. In the Raw Messages panel, let's inspect the /cmd\_vel topic.

final Studio layout

Now, driving the robot with your controller joysticks will publish those commands to the /cmd\_vel topic. When moving the joysticks on the controller, we can see the values in the Plot and Raw Messages panels change.

Try adding other panels (like the Diagnostics and Log panels) to view other data being published by your robot!

Get support on your robotics journey

If you liked this review, be sure to also check out our review of Duckiebot, another educational robotics platform geared towards robotics beginners.

Whether your goals are to develop the next great SLAM algorithm, conduct vision processing, or build a new control loop, a robotics platform like Duckiebot or the Yahboom Transbot will give you a great jumpstart on the process.

Join us on Slack to ask questions, give feedback, and get other recommendations on the other robot kits you should try!


When we talk about Foxglove Studio for visualizing your robotics data, we often envision troubleshooting a fully fledged robot – maybe something with a motor, wheels or rotating arms, and a variety of cameras, radar, and LIDAR sensors.

While this may be the case for many Foxglove Studio users, Studio can also help you visualize data earlier in your development process – long before you have a working robotics stack or an assembled robot.

To demonstrate this, let’s cover one of our lesser-known data sources in Foxglove Studio – the Velodyne LIDAR connection.

What is Velodyne LIDAR?

As a San Jose-based LIDAR technology company, Velodyne LIDAR develops sensors for the field’s leading robotics companies, for applications as wide-ranging as autonomous vehicles, mobile mapping, and delivery drones. These state-of-the-art sensors are directly responsible for bringing robotics technology into more visible arenas of our lives. Industry giants like NVIDIA, Clearpath Robotics, and Postmates are leveraging LIDAR technology to monitor traffic, streamline construction, and automate food delivery.

As ubiquitous as Velodyne LIDAR technology has become, it’s no surprise that many Foxglove Studio users are using these sensors on their robots to collect spatial data. If you want to get visual feedback on your sensor data before troubleshooting the rest of your robot, you can use Foxglove Studio to calibrate your hardware – even before you have a properly functioning robotics stack.

Connecting to your Velodyne hardware

To visualize data coming into your Velodyne LIDAR sensor, you’ll first need to connect your sensor to a local network with an Ethernet cable (often included in your Velodyne shipment). I'll be using the Puck sensor, but Studio supports visualizing data from any Velodyne LIDAR sensor.

Connected sensor

You can confirm everything is connected properly by visiting the Velodyne IP address in a browser (in our case, 192.168.2.201). From here, you can use the available web GUI to make sure your computer is on the same subnet as the Velodyne sensor.

Sensor IP information

The Velodyne IP address may be statically assigned or assigned from DHCP, depending on the sensor’s configuration. Consult the Velodyne manual for more information on the networking setup.

Visualizing your LIDAR data in Foxglove Studio

The sensor communicates by broadcasting UDP packets to 255.255.255.255 on port 2369 by default. To visualize this data, you’ll need to open the Foxglove Studio desktop app and “Open connection”:

Opening a connection in Foxglove Studio

From there, select the Velodyne LIDAR option. You’ll be prompted for a UDP port – unless you’ve previously changed the sensor’s UDP port yourself, you can leave the default value at 2369.

Setting the connection's UDP port in Foxglove Studio

Click “Open”. You shouldn’t see any changes yet. Add a 3D panel to your layout, and then open the topic picker to toggle on your LIDAR scan topic /velodyne\_points.

3D panel output

From there, you should start to see your sensor data displayed in your 3D panel! Move your sensor around to view different parts of your environment – see if you can identify what LIDAR returns correspond to what real-life obstacles.

Visualizing support for every stage of development

Whether they’re making cities smarter, people safer, or workplaces more efficient, Velodyne LIDAR’s state-of-the-art sensors have set the industry standard for collecting rich spatial data. If you’ve decided to integrate them into your own robotics build, we want you to be able to use Foxglove Studio to visualize their data.

Studio provides you with the building blocks to compose your own tools – no matter the workflow you’re tackling, the amount of data you have, or the stage of development you’re in. If you have a mature robotics build with multiple actuators, sensors, and other bells and whistles, you can build a complex layout to debug each level of your robotics stack. But if your robot is currently nothing more than a sensor mounted on some wheels, Studio can still help you get started. Open up that Velodyne LIDAR connection, and see the world as your robot does.


Opening a Velodyne LIDAR Connection

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