Autonomous and Adaptive Navigation for Terrestrial-Aerial Bimodal Vehicles
This work addresses the challenge of autonomous navigation for bimodal vehicles, which combine aerial mobility and ground endurance, offering incremental improvements in energy efficiency.
The paper tackles the problem of enabling complete autonomy for terrestrial-aerial bimodal vehicles by developing a navigation framework that includes a hierarchical motion planner and a unified motion controller, achieving 7x energy savings in terrestrial locomotion.
Terrestrial-aerial bimodal vehicles bloom in both academia and industry because they incorporate both the high mobility of aerial vehicles and the long endurance of ground vehicles. In this work, we present an autonomous and adaptive navigation framework to bring complete autonomy to this class of vehicles. The framework mainly includes 1) a hierarchical motion planner that generates safe and low-power terrestrial-aerial trajectories in unknown environments and 2) a unified motion controller which dynamically adjusts energy consumption in terrestrial locomotion. Extensive real-world experiments and benchmark comparisons are conducted on a customized robot platform to validate the proposed framework's robustness and performance. During the tests, the robot safely traverses complex environments with terrestrial-aerial integrated mobility, and achieves $7\times$ energy savings in terrestrial locomotion. Finally, we will release our code and hardware configuration for the reference of the community.