Artificial bee colony based optimization algorithm and its application on multi-drone path planning

Aiming at the problem of redundant local planning and long planning time of traditional artificial bee colony algorithms in the presence of constraints, this paper proposes an improved artificial bee colony algorithm. Based on the accuracy of the non-deterministic planning method and the rapidity of the two-way planning mechanism, non-deterministic search mechanisms and two-way planning methods are combined with traditional artificial bee colony algorithms to improve the algorithm’s tolerance and dynamic adaptability to map accuracy. In addition, to optimize the path-planning context, in this study, the constraints are represented as terrain regions. Finally, experimental simulations of single-drone and multi-drone path planning were performed using 2D and 3D plots. Simulation results show that this algorithm optimizes the path of the drone on the basis of meeting the needs of the drone to perform the mission and is easy to implement in engineering. At the same time, this paper compares the optimization algorithm with traditional path planning algorithms, traditional algorithms using a non-deterministic search mechanism, and traditional algorithms using a bidirectional planning method. The results show that this algorithm has better convergence and faster speed. At the same time, it can effectively balance global planning and local planning and can meet the needs of fast and accurate path planning.