基于ROS的机器人去跑偏板坯毛刺自主规划

Autonomous Planning for Robot to Remove Slab Burr Based on ROS

现代钢铁行业采用机器人切除板坯毛刺方法,但板坯在输送辊道中经常发生跑偏现象,采用示教方法无法适应去毛刺工作。针对该现象提出一种机器人结合深度相机去除跑偏板坯毛刺方法,首先在ROS系统中,利用MoveIt-Gazebo联合架构搭建去除跑偏板坯毛刺的仿真平台,然后通过深度相机进行点云三维重建,利用PCL点云的排列原理选取跑偏板坯第一角点,改变阈值识别中间点,运用向量计算识别第二角点,最终通过MoveGroup类以及笛卡尔运动规划算法,使机器人控制器自主接收定位到的角点信息并规划执行自主完成去除跑偏板坯毛刺工作。仿真结果表明:基于ROS的机器人结合深度相机去跑偏板坯毛刺方法是有效的,为后续的现场去跑偏板坯毛刺提供了新思路。

Robot has been used to remove slab burrs for the modern steel industry.However,the slabs often deviate from the track during transport.The teaching method is not suitable for deburring.With regard to this phenomenon,a new method for the combination of the robot and depth camera is proposed to remove deviated slab burrs.Firstly,the model is imported into ROS system.The Moveit-Gazebo joint architecture is used to set up simulation platform for removing slab burrs.Then,the 3D reconstruction of point cloud is carried out by depth camera.It takes permutation principle of PCL point cloud to select the first corner point of the deviated slab,and then to change the recognition threshold to identify intermediate point.And the second corner point is calculated and identified by vector.Finally,through MoveGroup and Cartesian motion planning algorithm,robot controller can autonomously receive the positioned information of corner point and plan to execute the removal of slab burrs.The simulation result shows that it is effective to use the combination of the robot and depth camera to remove slab burrs based on ROS,which provides a new idea for the subsequent slab burrs removal in practice.