SLAMcore algorithms will make use of several enhancements in ROS2 – specifically the upgraded Nav2 stack supporting fully autonomous, 3D navigation and enhanced support for embedded processors. The vision-based SLAM (simultaneous localisation and mapping) algorithm allows full 3D mapping and path planning within ROS2 and supports the development of semantic mapping to add labelling of objects within a map.
The fine-grain control of memory and processor functions enabled in ROS2 further enhances the efficiency of our algorithms allowing developers to use smaller, less power-hungry and more cost-effective embedded processors for SLAM. Bringing together highly accurate 3D maps with a proven software framework, plus the efficient use of power, memory and compute resources, makes SLAMcore and ROS2 a powerful combination for these emerging use cases.
ROS2 has been developed over the last couple of years to extend the benefits of the pioneering open-source Robot Operating System (ROS) into these rapidly emerging new robotics applications. For example, originally ROS was designed for single robots with workstation grade processors and no explicit real-time requirements. ROS2 adds in new capabilities that meet the more advanced and commercially focused nature of robotics today. These include support for teams of robots working together, operating in real-time without guaranteed high-performance networks, and the low-level tuning capabilities required to run on low-cost, embedded processors.
The SLAMcore SDK now supports ROS, ROS2 and C++ interfaces and is available now. It can be downloaded and deployed with standard hardware.
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