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.


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.


Jupyter Notebooks are a powerful interactive data analysis tool. We’ve made it easy to load, analyze, and transform your Foxglove Data Platform data with notebooks so you can gain additional insights into your robotics data.

Our sample Jupyter Notebook walks through loading data and performing a few basic operations to showcase some workflows. With the help of data analysis libraries like pandas, opencv, and matplotlib, you can write custom transformations to explore and experiment with your data.

matplotlib plot

Open the sample notebook locally or online.

Open In Colab

Binder

Jupyter Notebooks are just one of many ways you can leverage Foxglove Data Platform to analyze your data. We’ll continue to expand on Foxglove Data Platform to support a growing set of use cases to accelerate your robotics development.

Contact us to start storing and analyzing your own robotics data in a Foxglove Data Platform. If you have any questions about getting set up, you can reach out to us for a product demo or join our Slack community for questions and support.


Analyze Your Robotics Data with Jupyter Notebooks

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