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A Robot Obstacle Avoidance Method Based on Improved Genetic Algorithm

机译:基于改进遗传算法的机器人避障方法

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In order to improve the space obstacle avoidance ability of the robot and realize the optimal kinematics planning and design of the robot, a robot obstacle avoidance method is proposed based on improved genetic algorithm (GA), a robot space obstacle avoidance model based on genetic evolutionary adaptive guidance control is constructed. The constraint parameter model of obstacle avoidance control of robot is constructed, and the trajectory of space obstacle avoidance is described as the global optimization problem of genetic evolution. The pheromone released in genetic evolution is used as the guiding rule of space obstacle avoidance control of robot. The mechanical parameters of obstacle avoidance motion and trajectory tracking control parameters are obtained, and the control equations and dynamics equations of robot obstacle avoidance are constructed. The pheromones are broadcast according to the global optimization control rules of genetic evolution. The robot is driven to realize the space path optimization planning and to improve the obstacle avoidance algorithm. The simulation results show that the proposed algorithm is effective in avoiding obstacles, it can effectively avoid obstacles and improve the control performance of the robot.
机译:为了提高机器人的空间避障能力,实现机器人的最佳运动学设计与设计,提出了一种基于改进遗传算法(GA)的机器人避障方法,即一种基于遗传进化的机器人空间避障模型。构建了自适应制导控制。建立了机器人避障控制的约束参数模型,将空间避障的轨迹描述为遗传进化的全局优化问题。遗传进化中释放的信息素被用作机器人空间避障控制的指导原则。获得了避障运动的机械参数和轨迹跟踪控制参数,构造了机器人避障的控制方程和动力学方程。信息素是根据遗传进化的全局优化控制规则进行广播的。驱动机器人以实现空间路径优化规划并改进避障算法。仿真结果表明,该算法在避开障碍物方面是有效的,可以有效避开障碍物,提高机器人的控制性能。

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