Path planning of UAV in dynamic environment

In order to solve the problem of path planning in dynamic environment, a new method which introduced the time axis was given. Based on the configuration space (C space), the time axis was introduced to expand the C space to the configuration-time space (CT space), and the position of moving obstacles at all times could be expressed in the CT space. In the path generation stage, an improved ant colony algorithm was proposed. The heading information was introduced as heuristic information to the ant colony algorithm, and at the beginning of the algorithm ants could be guided to search the road map more efficiently. The simulation results show that the moving obstacles can be expressed well in the CT space. The improved ant colony algorithm is more efficient and it can converge to the best solution more quickly.