  Terrestrial and aerial bimodal vehicles have gained widespread attention due
to their cross-domain maneuverability. Nevertheless, their bimodal dynamics
significantly increase the complexity of motion planning and control, thus
hindering robust and efficient autonomous navigation in unknown environments.
To resolve this issue, we develop a model-based planning and control framework
for terrestrial aerial bi-modal vehicles. This work begins by deriving a
unified dynamic model and the corresponding differential flatness. Leveraging
differential flatness, an optimization-based trajectory planner is proposed,
which takes into account both solution quality and computational efficiency.
Moreover, we design a tracking controller using nonlinear model predictive
control based on the proposed unified dynamic model to achieve accurate
trajectory tracking and smooth mode transition. We validate our framework
through extensive benchmark comparisons and experiments, demonstrating its
effectiveness in terms of planning quality and control performance.
