Yard Robotics is on a mission to automate lawn care – to help people reclaim time for themselves, their families, and what matters to them most. As a replacement for traditional mowing and turf maintenance services, Yard Robotics deploys custom bots to map and traverse homeowners’ properties, leaving behind impeccably mown lawns and delighted customers.

The Yard team relies heavily on Foxglove's observability platform to understand and learn from their data. By integrating Foxglove with almost every core workflow, Yard has been able to scale their operations, accelerate their debugging workflows, and compress their time-to-market journey by nearly 6 months.

Adopting Foxglove

Accelerating autonomy software development with visualizations

While having broad test coverage is certainly critical to any software development, relying solely on manual testing methods to catch issues can be quite tedious.

With Foxglove visualizations, Yard engineers have a powerful shortcut to finding, triaging, and ultimately resolving issues with their autonomy stack. Resolving issues has become as simple as visualizing a bot’s recorded log data, or watching what the bots are doing in real-time.

“We’re a small company developing an autonomy stack from scratch. In the same way AI acts a multiplier for human beings, Foxglove is doing the same for our robotics team. It’s become a huge and irreplaceable accelerant to our development.” Divya Thakur, Founder of Yard Robotics

By publishing the relevant 3D visualization markers to denote important information – parallel lines for the track the bots are planning to follow, color-coded pins for different waypoints, gray “keep out” zones, red wheels for overheating motors, green bodies for bots that are ready to engage, etc. – Yard engineers can quickly glance at a 3D panel to understand how their nodes, machine learning models, and bots are all doing. Instead of having to check different parts of the logs, or even different panels in Foxglove, the team can simply look at a 3D scene to get everything they need – significantly speeding up the entire issue resolution and development process.

The team also relies heavily on the Plot panel, especially for making sense of a high volume of fast incoming data – for tuning PID controllers, tracking odometry values, and watching the control and command signals. Instead of manually reading through log data, Yard roboticists can now rely on these human-friendly representations of their data to quickly solve problems and seamlessly integrate their learnings into the next iteration of their autonomy software.

“Understanding our data without Foxglove sounds about as painful as building a robot stack without ROS.” Divya Thakur, Founder of Yard Robotics

Reducing onboarding time and improving training

When adopting ROS as their robotics framework, Yard engineers knew this decision could subject new team members to a particularly long and painful onboarding process. Every developer would be restricted to the same Linux platform – regardless of their own experience – and be forced to use notoriously clunky native developer tools like RViz. Onboarding with these tools alone – with their dense interfaces, hyper-technical controls, and various idiosyncrasies – could easily take weeks or months, quickly demotivating developers looking to make a difference on the team.

With Foxglove, Yard roboticists hit the ground running within a few days. Because it is a cross-platform app, engineers can connect Foxglove to their ROS stack using a Linux, Windows, or macOS machine. Because it has an intuitive interface that doesn’t require any niche domain knowledge to navigate, even engineers without any prior experience can get up-to-speed on common ROS paradigms like topics, messages, and visualization markers.

Less technical team members can also use Foxglove to make significant contributions to the team. While they may need a teammate to configure a layout for them, they can help triage incidents, remotely monitor deployed bots, and resolve issues once that workspace is set up.

Enabling remote assistance and monitoring

In addition to using Foxglove for visualization and debugging, Yard also uses the app as its primary back-end remote monitoring system.

Yard’s bots communicate over LTE to a back-end that pipes all data into a single ROS master. Remote assistance technicians can then connect to this data source with Foxglove to get a 20,000 feet view of their fleet. They can see all their robots on maps throughout the city and get a sense of how the fleet is doing – where every bot is located, the progress it’s making, and its planned route.

Remote monitoring has enabled Yard to avoid sending technicians on-site to supervise the bots. Those same technicians can now sit in an air-conditioned room with a laptop and remotely handle hardware and software issues as they arise.

Outcome

Integrating Foxglove into their core workflows has streamlined work across Yard’s entire team and dramatically accelerated their progress from prototype to production. It has empowered engineers to focus on their autonomy software, get robots to production, and scale the fleet. It’s made the business of troubleshooting incidents out in the field – and iterating with that feedback – as simple as clicking a few buttons in a Foxglove layout.

Instead of being restricted to a lab somewhere, Yard bots are out in the field every day, mowing more lawns and serving more customers. Their real-world experience is powering the R&D needed for the next iteration.

“Foxglove has been a game-changer for us. Investors are surprised with the progress we’ve made with relatively few engineering resources, and it's because we are leveraging tools like Foxglove.”Divya Thakur, Founder of Yard Robotics

With Foxglove, Yard has been able to maintain their breakneck rate of development and keep themselves on track towards their mission. While they’ve started with residential areas as their operational domain, the team is excited to target more complicated tasks and expand their fleet as they iterate on their tech – using Foxglove every step of the way.