周友行, 何清华, 谢习华. 基于遗传算法的凿岩机器人孔序规划[J]. 机器人, 2002, 24(1): 62-65.
引用本文: 周友行, 何清华, 谢习华. 基于遗传算法的凿岩机器人孔序规划[J]. 机器人, 2002, 24(1): 62-65.
ZHOU You-hang, HE Qing-hua, XIE Xi-hua. APPLICATION OF GENETIC ALOGORITHM TO BORE PLANNING OF THE TUNNEL DRILLING ROBOT[J]. ROBOT, 2002, 24(1): 62-65.
Citation: ZHOU You-hang, HE Qing-hua, XIE Xi-hua. APPLICATION OF GENETIC ALOGORITHM TO BORE PLANNING OF THE TUNNEL DRILLING ROBOT[J]. ROBOT, 2002, 24(1): 62-65.

基于遗传算法的凿岩机器人孔序规划

APPLICATION OF GENETIC ALOGORITHM TO BORE PLANNING OF THE TUNNEL DRILLING ROBOT

  • 摘要: 本文运用遗传算法规划凿岩机器人钻孔任务序列,通过判断机器人的多关节钻臂上每一关节其运动方向在彼此相邻的三个钻孔位置上的变化趋势,用数值0表示某一关节运动方向变化趋势在相邻三个钻孔上不一致,数值1表示此关节运动方向变化趋势在相邻三个钻孔上一致.并根据具体的工作情况对描述值进行修正.在此基础上设计了一个基于关节水乎上来规划凿岩机器人随机钻孔孔序的适应度函数,从而使整个钻孔孔序规划算法算法简单,收敛速度快,能寻求到较优的钻孔孔序,其结果能满足实际工作的需要.此方法对于其他类型的关节型机器人的任务和轨迹规划也具有一定的借鉴意义.

     

    Abstract: The bore assignment of the multi-joint tunnel-drilling robot is stochastic sequence; the bore planning is very difficulty. The application of genetic algorithm to bores planning of the multi-joint tunnel-drilling robot is discussed in this paper, we introduce the direction change of every robot joint from three contiguous bores as numerical value, adopt numerical value "0" to describe the difference movement trend and "1" consistent trend, and can modify the numerical value on the foundation of the fact condition, then present an adaptation function on the basis of the change trend of joint. Simulation shows that applying this adaptation function can find out the global optimal solution and obtain fast convergence velocity. As a result, the conclusion can be satisfied with the need of work. This method can be effectively used for reference to other multi-robot system.

     

/

返回文章
返回