  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.
