Research on millimeter-wave radar-assisted multi-agent collaborative localization and mapping

With the development of autonomous driving technology, the low-altitude Internet of things has gradually become a key focus of national industrial innovation. High-precision and highly adaptable simultaneous localization and mapping are crucial for the intelligent operation of unmanned systems. However, the limited perception capabilities of a single agent and the susceptibility of visual sensors to interference make it challenging for traditional methods to meet the demands of real-time localization and mapping in complex and dynamic environments. To enhance the accuracy and adaptability of localization and mapping, an innovative millimeter-wave radar-assisted multi-agent collaborative localization and mapping scheme was presented. This scheme deeply explored the multi-dimensional features of millimeter-wave radar in the time, space, and Doppler domains, effectively filtering and collecting reliable point cloud information to achieve local odometry and local map construction. With shared local map information, a collaborative global optimization mechanism was designed to achieve precise localization and mapping. Experimental results demonstrate that this scheme effectively ensures the robustness and accuracy of the system.