While the SOS-based formulation offers a powerful method for ensuring collision-free trajectories in cluttered environments, there are potential limitations and drawbacks that should be considered. One limitation is the computational complexity associated with solving large-scale SOS optimization problems, especially in real-time applications or environments with a high number of obstacles. This could lead to increased computation time and resource requirements. To address this, future work could focus on developing more efficient algorithms or approximations to streamline the optimization process. Additionally, the SOS-based formulation may struggle with non-convex or highly complex geometries, limiting its applicability in certain scenarios. Exploring hybrid approaches that combine SOS programming with other optimization techniques could help overcome these limitations and enhance the method's robustness and versatility.