改进的快速扩展随机树在航迹规划中的应用

Trajectory planning using improved rapidly-exploring random tree

通过在快速扩展随机树(rapidly-exploring random tree)算法的基础上融入状态-时间空间(state-timespace)的思想,使改进后的算法能够有效地处理动态环境中的航迹规划问题。仿真试验首先采用四元素法建立航天飞行器的六自由度动力学模型,在三维空间中验证该算法搜索高维空间的能力。其次运用改进的算法在动态环境中进行航迹规划试验,证明了该算法的有效性。

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.