动态环境下基于视觉定位的仓储搬运机器人避障控制方法

Research on the Mix Ratio Optimization and Construction Technology of Porous Concrete

仓储搬运机器人避障研究过程中,容易受到机器人运动环境干扰,使得该方法实施后避障运动路径较长。因此,提出动态环境下基于视觉定位的仓储搬运机器人避障控制方法。通过机器人身上安装的双目摄像机采集动态与环境信息,定位到周边环境中障碍物位置。利用自组织可增长特征映射图(GSOM)进一步处理障碍物定位信息,绘制仓储搬运机器人运动环境地图。然后,运用人工势场法模拟机器人工作空间,得出动态环境下机器人避障规划路径。最后,计算出机器人避障转动控制目标角度,再结合PID闭环控制思想实现避障反馈控制。实验结果表明:在60m 2的室内环境中,将新研究方法应用到多种类型的动态环境中完成避障控制,所产生的机器人避障运动路径最长仅为3.5m,更好地满足了仓储搬运机器人工作要求。

The study used a three-level seven-factor orthogonal experimental design to investigate the factors affecting the compressive strength and permeability of porous concrete,including target porosity,water-to-cement ratio,aggregate type,silica fume content,fly ash content,and mixing method.The research results showed that the main and secondary factors affecting compressive strength were target porosity,aggregate type,water-to-cement ratio,mixing method,silica fume content,and fly ash content,respectively.The factors affecting permeability were target porosity,aggregate type,fly ash content,water-to-cement ratio,mixing method,and silica fume content,respectively.This study provides scientific basis and practical guidance for the design and application of porous concrete.