An innovative sort of mobility platform that can both drive and fly is the air-ground robot. The need for an agile flight cannot be satisfied by traditional path planning techniques for air-ground robots. Prior studies had mostly focused on improving the energy efficiency of paths, seldom taking the seeking speed and optimizing take-off and landing places into account. A robot for the field application environment was proposed, and a lightweight global spatial planning technique for the robot based on the graph-search algorithm taking mode switching point optimization into account, with an emphasis on energy efficiency, searching speed, and the viability of real deployment. The fundamental concept is to lower the computational burden by employing an interchangeable search approach that combines planar and spatial search. Furthermore, to safeguard the health of the power battery and the integrity of the mission execution, a trap escape approach was also provided. Simulations are run to test the effectiveness of the suggested model based on the field DEM map. The simulation results show that our technology is capable of producing finished, plausible 3D paths with a high degree of believability. Additionally, the mode-switching point optimization method efficiently identifies additional acceptable places for mode switching, and the improved paths use less time and energy.

翻译：一种创新的可行驶与飞行的移动平台是空地机器人。传统的空地机器人路径规划技术无法满足敏捷飞行的需求。先前的研究主要集中在提高路径的能量效率，很少考虑搜索速度以及优化起飞和降落地点。针对现场应用环境提出了一种机器人，并基于考虑模态切换点优化的图搜索算法，设计了一种轻量级的全局空间规划技术，其重点在于能量效率、搜索速度以及实际部署的可行性。核心思想是通过采用结合平面搜索与空间搜索的可互换搜索方法来降低计算负担。此外，为了保障动力电池的健康和任务执行的完整性，还提供了一种陷阱逃脱策略。基于现场DEM地图进行了仿真，以测试所提模型的有效性。仿真结果表明，我们的技术能够生成完整且可信度高的三维路径。此外，模态切换点优化方法有效识别了更多合适的模态切换地点，并且优化后的路径消耗的时间和能量更少。