Improved UCAV Attack Trajectory Planning Algorithm Based on GWO and Dubins Curve

Abstract

AMR is widely used in factories to replace manual labor to reduce costs and improve efficiency. However, it is often difficult for logistics robots to plan the optimal trajectory and unreasonable trajectory planning can lead to low transport efficiency and high energy consumption. In this paper, we propose a method to directly calculate the optimal trajectory for short distance on the basis of the Dubins set, which completes the calculation of the Dubins path. Additionally, as an improvement of Dubins path, we smooth the Dubins path based on clothoid, which makes the curvature varies linearly. AMR can adjust the steering wheels while following this trajectory. The experiments show that the Dubins path can be calculated quickly and well smoothed.

A new improved optimizer adjusted by elite adjustment strategy

“…Dong et al [11] have developed an action recognition method that utilizes radar signals and incorporates an enhanced GWO-SVM algorithm. Huang et al [12] introduced an enhanced algorithm for planning attack trajectories of Unmanned Combat Aerial Vehicles (UCAVs). The algorithm incorporates the principles of GWO and Dubins CurveMeng et al [13] introduced a method for predicting faults in capacitors of power converters by employing CEEMDAN and GWO-RELM.Singh et al [14] proposed GWO and a hybrid PSO-GWO approach for addressing the reliability optimization and redundancy allocation problem.…”