Jason Ellis shows how onboard Simultaneous Localization and Mapping (SLAM) technology affects the efficiency of mobile mapping data collection.
SLAM (Simultaneous Localization and Mapping) is a technique used in robotics and computer vision to simultaneously estimate the position of a robot or camera and build a map of the environment. The benefit of SLAM is that it allows a robot or camera to navigate and understand its surroundings without the need for pre-existing maps or external localization systems. This makes it a powerful tool for autonomous navigation and exploration in unknown or changing environments. Additionally, SLAM algorithms can improve the accuracy of localization and mapping by fusing data from multiple sensors, such as cameras, lidar, and IMU.
The new Leica Pegasus TRK mobile mapping system includes SLAM onboard. This gives the system a powerful way to carry its position when working in areas that do not have access to satellites for GNSS positioning, such as large cities. These GNSS-denied environments have previously been off-limits to mobile mapping data collection.
Jason Ellis recently tested the onboard SLAM capabilities of the Pegasus TRK in downtown Chicago by driving on Wacker Dr. and then underground in the tunnels. “Two passes, each over 1 mile in length, and the SLAM worked like a charm,” he says. “The data lines up nicely even with some significant trajectory changes underground.”
The data in the video above did not have any adjustments applied to it. The SLAM capabilities handled the alignment.
About the Author:
For over 20 years Jason Ellis has been an agent of change by way of technology and a passionate advocate of all things geospatial. Every day he works to help organizations transform their potential by exploring and implementing mobile reality capture solutions. As the North American mobile mapping sales and technical consultant for Leica Geosystems, he works closely with collaborators who are driving reality capture and helping to shape the landscape of the industry. Follow Jason on LinkedIn.
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