Collision-free polynomial trajectory generation method based on unmanned aerial vehicle

Abstract

The invention discloses a collision-free polynomial trajectory generation method based on an unmanned aerial vehicle, and the method comprises the steps: 1), carrying out the path search through employing an improved RRT * path search algorithm with the addition of elliptic constraint, and obtaining a series of barrier-free points; 2) using a trapezoidal time allocation criterion to allocate time for a polynomial trajectory passing through a series of barrier-free points; (3) planning a polynomial track meeting the time distribution by using a Minimum snap algorithm; 4) if detecting that the polynomial trajectory collides, regenerating the polynomial trajectory by using an interpolation method, and finally obtaining a collision-free polynomial trajectory; according to the method, the speed of convergence of the RRT * path search algorithm to the shortest path is greatly accelerated by adding the elliptic constraint; a trapezoidal time allocation criterion is used, so that the quality of a polynomial trajectory generated by a Minimum snap algorithm is improved; when the collision of the generated polynomial trajectory is detected, regenerating the polynomial trajectory by using an interpolation method to ensure that the trajectory does not collide with an obstacle; the method is wide in applicability and has a wide application prospect.

Description

technical field [0001] The invention relates to the technical field of motion planning, in particular to a collision-free polynomial trajectory generation method based on an unmanned aerial vehicle. Background technique [0002] In recent years, with the maturity of UAV algorithms and the continuous improvement of hardware computing power, the application of UAVs has become more extensive, and the research on UAV motion planning has been carried out. The mainstream motion planning is composed of It consists of two aspects: path search and trajectory planning. [0003] The purpose of path search is to obtain an unobstructed path connecting the starting point to the ending point. Typical algorithms include the A* algorithm and the RRT* algorithm; the advantage of the A* algorithm is that the generated path is globally optimal, but the disadvantage is that the time complexity is relatively high. It is not suitable for online search; the advantage of the RRT* algorithm is that ...

AI Technical Summary

Problems solved by technology

The typical algorithm is the Minimum snap algorithm. Its advantage is that the generated trajectory is smooth and consumes the least energy, but there are two disadvantages: one is the lack of an effective trajectory time allocation strategy, which makes the generated trajectory prone to "knotting". Reduce the quality of the trajectory; the second is that when the generated trajectory collides with obstacles, there is no effective way to re-plan the trajectory and regenerate the trajectory that does not collide with obstacles

Images