基于改进的烟花-蚁群算法和B样条曲线的农业机器人路径规划

根据蚁群算法收敛速度较慢,易陷入局部最优等问题,提出了一种改进烟花-蚁群(improved fireworks-ant colony algo-rithm,IFWA-ACO)混合算法,解决静态环境下农业机器人的路径规划问题,首先针对基本烟花的交互机制和选择策略做出改进,提出爆炸与迁移相结合的策略以及密度峰值火花、探测火花概念,提升烟花算法寻找最优解的能力,然后把改进烟花算法得到的最短路径作换算成蚁群算法中的信息素加强值,从而避免蚁群盲目搜索,最后采用B样条插值方法进行曲线化拟合,生成平滑路径,有利于机器人平稳行进.试验仿真结果表明,IFWA-ACO算法能快速的规划出机器人的最优路径,降低农业机器人能耗,提高工作效率.

Research on agricultural robot path planning based on improved firework-ant colony algorithm and B-spline curve

Based on ant colony algorithm convergence speed is slow, easy falling into the most superior problem, an improved fireworks - mixed ant colony algorithm, solving the problem of agricultural robot path planning under static environment, first against the basic interaction mechanism of fireworks and selection strategy to make improvements, to put forward the strategies of the blast combined with migration and density peak sparks, detection concept, improve the ability in the fireworks algorithm to find the optimal solution, and then improve the fireworks in the conversion algorithm of the shortest path for the pheromone of ant colony algorithm to strengthen value, thereby avoiding ant colony search blindly, finally using b-spline interpolation method to curve fitting, and generate a smooth path,Conducive to the smooth progress of the robot.The simulation results show that ifwa-aco algorithm can quickly plan the optimal path of the robot, reduce the energy consumption of the agricultural robot and improve the working efficiency.