Paper ID: 2210.16875

A Multi-modal Deformable Land-air Robot for Complex Environments

Xinyu Zhang, Yuanhao Huang, Kangyao Huang, Xiaoyu Wang, Dafeng Jin, Huaping Liu, Jun Li

Single locomotion robots often struggle to adapt in highly variable or uncertain environments, especially in emergencies. In this paper, a multi-modal deformable robot is introduced that can both fly and drive. Compatibility issues with multi-modal locomotive fusion for this hybrid land-air robot are solved using proposed design conceptions, including power settings, energy selection, and designs of deformable structure. The robot can also automatically transform between land and air modes during 3D planning and tracking. Meanwhile, we proposed a algorithms for evaluation the performance of land-air robots. A series of comparisons and experiments were conducted to demonstrate the robustness and reliability of the proposed structure in complex field environments.

Submitted: Oct 30, 2022