  The efficiency and accuracy of mapping are crucial in a large scene and
long-term AR applications. Multi-agent cooperative SLAM is the precondition of
multi-user AR interaction. The cooperation of multiple smart phones has the
potential to improve efficiency and robustness of task completion and can
complete tasks that a single agent cannot do. However, it depends on robust
communication, efficient location detection, robust mapping, and efficient
information sharing among agents. We propose a multi-intelligence collaborative
monocular visual-inertial SLAM deployed on multiple ios mobile devices with a
centralized architecture. Each agent can independently explore the environment,
run a visual-inertial odometry module online, and then send all the measurement
information to a central server with higher computing resources. The server
manages all the information received, detects overlapping areas, merges and
optimizes the map, and shares information with the agents when needed. We have
verified the performance of the system in public datasets and real
environments. The accuracy of mapping and fusion of the proposed system is
comparable to VINS-Mono which requires higher computing resources.
