Trajectory planning using improved rapidly-exploring random tree

A tool called rapidly-exploring random tree is presented. It is suitable for solving trajectory planning problem in a dynamic environment based on the concept of state-time space. Firstly, the experiments are made in 3-dimensional space using a six-degree-of freedom spacecraft model represented by unit quaternion. Experimental results indicate that the proposed scheme has the capability of searching high-dimensional space. Secondly, an experiment is performed in a dynamic environment with moving obstacles with known trajectories, and the result shows that the improved algorithm is effective.