Research on 3D Trajectory Planning Based on the IAPF-CRRT∗ Algorithm

In order to solve the problems of RRT∗ algorithm, such as large sampling randomness, low search efficiency, and great impact on the quality of search trajectory due to the limited number of iterations, a RRT*-Connect algorithm combining improved artificial potential field (IAPF-CRRT∗ algorithm) was proposed to realize trajectory planning in complex three-dimensional environment. In the direction of point expansion, improved gravitational and repulsive fields were introduced to guide the point expansion process and limit the randomness of the expansion. In this study, a dynamic step length selection method was proposed for the random tree point step length, and whether the current point was in the repulsive field was discussed, so that different expansion step length could be determined. The results showed that compared with RRT∗ algorithm, the designed IAPF-CRRT∗ algorithm had less planning time, shorter trajectory length, higher point utilization rate, which had significantly improved the planning efficiency.