SLAM (Simultaneous Localization and Mapping) using point cloud data.

The realization of a "digital twin" where the physical site and virtual space collaborate with each other!

SLAM (Simultaneous Localization and Mapping) refers to a technology that allows mobile entities such as robots to simultaneously perform self-localization and create environmental maps. Areas where SLAM is beneficial include autonomous driving and autonomous mobility systems. When constructing an autonomous driving system, it can be broadly divided into three categories: "perception," "decision-making," and "action," with SLAM being a crucial technology in the "perception" category. Specifically, it acquires point cloud data from sensors such as LiDAR and performs specific tasks, such as avoiding obstacles, using the map information and self-localization constructed by SLAM. 【Features】 - Supports autonomous operation of construction and heavy machinery by using LiDAR and other technologies for spatial recognition (self-location, situational awareness). - Enables self-localization even in environments where GPS cannot be used. *For more details, please refer to the related links or feel free to contact us.

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