Adaptive SE(2)/SE(3) Switching for Visual-Inertial-wheel SLAM: Motion Aware Optimization for Heterogeneous Robotic Platforms

Ground-based mobile robots predominantly exhibit planar motion SE(2), while aerial vehicles and robots navigating irregular terrain require full 3D pose estimation SE(3). Fixed motion model representations lead to either overparameterization during planar operation or under-parameterization during spatial maneuvers, reducing computational efficiency and degrading estimation accuracy. We propose an adaptive switching mechanism for visual-inertial-wheel odometry SLAM that automatically transitions between SE(2) and SE(3) optimization based on real-time motion characteristics. The method monitors vertical trajectory deviation within a sliding keyframe window and employs a sigmoid-based weighting function to smoothly adjust the influence of inertial and wheel odometry measurements. Evaluation on the OpenLORIS dataset demonstrates that the adaptive approach achieves competitive accuracy while reducing computational complexity during planar motion phases, with seamless transitions preserving numerical stability in gradient-based optimization.

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