期刊文献+

基于双目视觉的机器人机械臂运动轨迹自动化检测研究

Research on Automatic Detection of Robot Robotic Arm Motion Trajectory Based on Binocular Vision
下载PDF
导出
摘要 研究基于双目视觉的机器人机械臂运动轨迹自动化检测方法,为其规划最佳运动轨迹。通过平行光轴理论建立立体视觉模型,提取机器人机械臂的抓取目标的颜色信息,经HSV阈值分割获取机器人机械臂的抓取目标的三维坐标,通过NURBS曲线检测机器人机械臂到抓取目标三维坐标的运动轨迹,并以机械臂工作时间、关节加速度、关节平均跃度最小为目标,结合关节的速度、加速度、角加速度运动约束,进行机器人机械臂轨迹优化,经遗传算法求解获取最佳机械臂运动轨迹优化结果。实验结果表明,该方法可实现目标物体的精准定位,为机器人机械臂规划最佳运动轨迹,提升机械臂运动效率和关节运动平滑性、降低关节能耗,完成抓取目标的精准抓取。 Research on an automated detection method for robot robotic arm motion trajectory based on binocular vision,and plan the optimal motion trajectory for it.By using the theory of parallel optical axis,a stereo vision model is established to extract the color information of the grasping target of the robot robotic arm.The three-dimensional coordinates of the grasping target of the robot robotic arm are obtained through HSV threshold segmentation.The motion trajectory of the robot robotic arm to the grasping target three-dimensional coordinates is detected through NURBS curves.The goal is to minimize the working time,joint acceleration,and average joint jump of the robotic arm,combined with the speed and acceleration of the joints angular acceleration motion constraint is used to optimize the trajectory of the robot manipulator,and the optimal trajectory of the manipulator is obtained by solving the genetic algorithm.The experimental results show that this method can achieve precise positioning of the target object,plan the optimal motion trajectory for the robotic arm,improve the efficiency and smoothness of the arm motion,reduce joint energy consumption,and achieve precise grasping of the target.
作者 李喜龙 LI Xilong(School of Mechanical and Materials Engineering,Xi’an University,Xi’an 710065,China)
出处 《自动化与仪表》 2024年第3期56-60,共5页 Automation & Instrumentation
基金 西安市科技局科技计划项目(22FWQY04)。
关键词 双目视觉 机械臂 运动轨迹 自动化 NURBS曲线 遗传算法 binocular vision mechanical arm motion trajectory automation NURBS curves genetic algorithm
  • 相关文献

参考文献10

二级参考文献85

共引文献63

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部