  Most Simultaneous localisation and mapping (SLAM) systems have traditionally
assumed a static world, which does not align with real-world scenarios. To
enable robots to safely navigate and plan in dynamic environments, it is
essential to employ representations capable of handling moving objects. Dynamic
SLAM is an emerging field in SLAM research as it improves the overall system
accuracy while providing additional estimation of object motions.
State-of-the-art literature informs two main formulations for Dynamic SLAM,
representing dynamic object points in either the world or object coordinate
frame. While expressing object points in a local reference frame may seem
intuitive, it may not necessarily lead to the most accurate and robust
solutions. This paper conducts and presents a thorough analysis of various
Dynamic SLAM formulations, identifying the best approach to address the
problem. To this end, we introduce a front-end agnostic framework using GTSAM
that can be used to evaluate various Dynamic SLAM formulations.
