Aiming at the multiconstraint complex problem of path planning, a hybrid algorithm with fast convergence and fast obstacle avoidance is proposed. According to the actual aircraft, a multiconstrained path cost model with seven components is constructed and defined the parameters and penalty factors of each part. To improve the sensitivity of each part of the trace planning cost function, according to the inconsistency of the cost index unit and measurement range, the expert scoring method is used to configure and normalize the index with weight. Make full advantage of the ACO algorithm and the artificial potential field algorithm to form the ACA hybrid algorithm, a pheromone heuristic function improvement method is proposed, and a control factor is introduced. The proposed model and planning algorithm are simulated based on the MATLAB platform environment, and it is shown by simulations that the hybrid algorithm has obvious advantages in terms of motion trajectory smoothness, number of iterations, and minimum path cost .It well solved the practical application problem of fast path planning convergence and fast avoiding obstacles in the complex environment.

中文翻译：

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基于ACA混合算法的复杂多约束路径规划研究

针对路径规划的多约束复杂问题，提出了一种快速收敛和快速避障的混合算法。根据实际飞行器，构建了一个包含七个分量的多约束路径成本模型，并定义了各个部分的参数和惩罚因子。为提高轨迹规划成本函数各部分的敏感性，根据成本指标单位和度量范围的不一致，采用专家评分法对指标进行配置和归一化加权。充分利用ACO算法和人工势场算法形成ACA混合算法，提出信息素启发式函数改进方法，并引入控制因子。