Kaarta Cloud is a platform to process, store, and share 3D spaces. Paired with high-quality lidar to capture the environment in 3D, the data is uploaded into Kaarta Cloud to quickly and easily process it into a point cloud for use.
The platform supports three Velodyne sensors - the Ultra Puck, Puck, and HDL-32E - that provide high-quality resolution and performance along with a full 360-degree environmental view to deliver real-time 3D data. After using a Velodyne sensor to scan the environment, Kaarta's proprietary Kaarta Engine uses simultaneous localization and mapping (SLAM) algorithms to instantaneously process lidar data into a registered point cloud map.
This enables users to produce accurate, measurable 3D models and vivid visual representations of complex environments, ranging from buildings and infrastructure to dangerous and hard-to-reach areas.
"Kaarta Cloud opens up access to Kaarta's advanced SLAM-based technology to Velodyne’s lidar sensors, in addition to Kaarta systems," says Kevin Dowling, CEO, Kaarta. "It provides a fast, flexible workflow to manage mobile mapping 3D data from field capture to finished data."
Jon Barad, Vice President of Business Development, Velodyne Lidar says, "Kaarta Cloud is an exciting innovation for the growing ecosystem of software tools that allow Velodyne’s lidar customers and partners to produce awesome 3D digital twins. Online SLAM processing of lidar data expands the capabilities, scope, ease of use and speed at which the user community can leverage Velodyne's sensors. This will help unlock the tremendous potential for lidar-based innovation and mapping applications."
Mobile scanning systems are continually advancing and the possibilities for use are expansive, say the companies. There is growing interest in lidar imaging for post-earthquake assessment, surveys of damaged buildings, aiding first responders in emergency situations and more. As the applications and sophistication of these tools grow, so does the size and complexity of the data collected, necessitating new ways of managing massive data sets that can be in excess of one billion points.