基于高斯基模糊神经网络的移动焊接机器人焊缝实时跟踪

对所研制的焊接移动机器人建立了运动学模型并设计了基于高斯基模糊神经网络的焊缝跟踪控制器.采用Denavit-Hartenberg(D-H)齐次坐标变换法分析了机器人本体和滑块对焊炬点位姿的运动学行为,建立了较为完整地运动学模型.在此基础上.提出了采用高斯基模糊神经网络实现焊缝实时跟踪的方法.采用高斯函数作为隶属函数,以滑块位置和小车方位角作为输入,焊炬的转向调整角作为输出,利用神经网络的自学习和自适应能力,实现模糊隶属函数和控制规则的在线修改.焊缝跟踪试验验证了所设计控制器的有效性,其跟踪精度可始终控制在±0.5 mm以内,满足实际焊接工程的需要.

Real-time seam tracking based on fuzzy-gaussian neural netwrok for welding mobile robot

Kinematics modeling of the developed welding mobile robot was presented and a real time seam tracking algorithm based on fuzzy neural network was proposed.At first, the kinematics behavior of mobile robot body and cross sliders action to the welding torch were investigated by the Denavit-Hartenberg Homogeneous transformation method, and a full kinematics model was established. And then a seam tracking controller based on fuzzy-gaussian neural network (FGNN) was described by applying a Gaussian function as an activation function, taking lateral slider position and heading angle of the robot as input signals, and the adjusted angle for welding torch as output, a specialized learning architecture was used so that membership function ould be tuned in real time by applying the backpropagation algorithm of FGNN controller.The experiment results show that the proposed controller has excellent tracing accuracy (within±0.5 mm), and can satisfy the requirement of practical welding project.