Real-world LiDAR, mapping and video datasets for robotics and Physical AI
Robotic Data captures and processes real-world sensor data for autonomous vehicles, robots and drones. Its stack pairs a .NET/C# and React application layer with a robotics toolchain (ROS 2, GTSAM, Open3D, OpenCV, GDAL), and research-heavy hiring targets SLAM pipelines and cross-session map alignment. Recurring pain points around drift, localization and point cloud registration show mapping accuracy at scale is the core engineering bottleneck.
Robotic Data is a privately held company headquartered in Austin, Texas, founded in 2017 and employing 201–500 people. It produces real-world datasets used to train autonomous vehicles, humanoid robots, drones and industrial automation systems. Its work spans LiDAR and mobile mapping, 3D and 4D mapping, digital twins and aerial geospatial programs, plus first-person video collection of human household activities. The company hires across the United States, United Kingdom, Portugal and Mexico.
Robotic Data uses C#, .NET, ASP.NET Core, React and TypeScript, with SQL Server, PostgreSQL and Redis, on AWS and Azure, plus robotics tools like ROS 2, GTSAM, Open3D, OpenCV and GDAL.
Current work includes new SLAM pipelines, sensor fusion combining LiDAR, cameras, GNSS and IMU, cross-session map alignment, aerial geospatial programs and first-person video collection of household activities.
Robotic Data hires in the United States, United Kingdom, Portugal and Mexico, with engineering and research roles leading the mix.
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Robotic Data's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.