  This survey paper presents a comprehensive overview of the latest
advancements in the field of Simultaneous Localization and Mapping (SLAM) with
a focus on the integration of symbolic representation of environment features.
The paper synthesizes research trends in multi-agent systems (MAS) and
human-machine teaming, highlighting their applications in both symbolic and
sub-symbolic SLAM tasks. The survey emphasizes the evolution and significance
of ontological designs and symbolic reasoning in creating sophisticated 2D and
3D maps of various environments. Central to this review is the exploration of
different architectural approaches in SLAM, with a particular interest in the
functionalities and applications of edge and control agent architectures in MAS
settings. This study acknowledges the growing demand for enhanced human-machine
collaboration in mapping tasks and examines how these collaborative efforts
improve the accuracy and efficiency of environmental mapping
