先验性虚拟排斥力约束下带电作业机械臂轨迹控制  

Trajectory Control of Live Working Robotic Arm under Prior Virtual Repulsive Force Constraint

作　　者：孙涛 张似丰 杨浩 SUN Tao;ZHANG Sifeng;YANG Hao(Guannan County Power Supply Branch of State Grid Jiangsu Electric Power Co.,Ltd.,Lianyungang 223500,China)

机构地区：[1]国网江苏省电力有限公司灌南县供电分公司,江苏连云港223500

出　　处：《微型电脑应用》2024年第7期157-159,共3页Microcomputer Applications

摘　　要：由于带电作业中的机械臂需避开电力设备和障碍物,使得后验性约束条件的稳定性较差,进而导致控制曲线误差较大。对此,提出虚拟排斥力约束下的带电作业机械臂运动控制方法。对带电机作业机械臂关节的功能和势能进行计算。使用人工势场法进行障碍物检测,并结合机械臂关节的功能和势能计算具有先验性属性的虚拟排斥力。基于虚拟排斥力对机械臂与障碍物之间距离设置相应的约束。基于设置的约束条件,采用CPG神经网络构建机械臂的运动控制模型。实验结果表明,所提方法的机械臂运动控制位置与目标位置几乎一致,完美贴合目标曲线,并且具有快速的响应能力。Due to the need for the robotic arm in live working to avoid electrical equipment and obstacles,the stability of posterior constraints is poor,and may result in significant control curve errors.Hence,a motion control method for live working robotic arms under virtual repulsion constraints is proposed.It calculates the function and potential energy of the joint of the robotic arm with a motor.The artificial potential field method is used for obstacle detection,and the virtual repulsion force with prior properties is calculated based on the function and potential energy of the robotic arm joint.It sets corresponding constraints on the distance between the robotic arm and the obstacle based on virtual repulsion.Based on the set constraints,a motion control model of the robotic arm is constructed using a CPG neural network.The experimental results show that the proposed method’s robotic arm motion control position is almost identical to the target position,perfectly fits the target curve,and has fast response ability.

关 键 词：带电作业 虚拟排斥力 CPG神经网络 轨迹控制 

分 类 号：TP247[自动化与计算机技术—检测技术与自动化装置]