论文标题
基于空间坐标的识别的3多机器人组的模型预测控制设计
Model Predictive Control Design of a 3-DOF Robot Arm Based on Recognition of Spatial Coordinates
论文作者
论文摘要
本文使用模型预测控制（MPC）来优化三度（DOF）机器人臂的输入扭矩，从而使其能够运行到目标位置并准确抓住对象。单眼相机首先用于识别物体的颜色和深度。然后，通过坐标转换组合了对象的反向运动学计算和对象的空间坐标，以获取每个伺服器所需的旋转角度。最后，得出了机器人臂结构的动态模型，并应用模型预测控制以模拟伺服器的最佳输入扭矩以最大程度地减少成本函数。
This paper uses Model Predictive Control (MPC) to optimise the input torques of a Three-Degrees-of-Freedom (DOF) robotic arm, enabling it to operate to the target position and grasp the object accurately. A monocular camera is firstly used to recognise the colour and depth of the object. Then, the inverse kinematics calculation and the spatial coordinates of the object through coordinate transformation are combined to get the required rotating angle of each servo. Finally, the dynamic model of the robotic arm structure is derived and the model predictive control is applied to simulate the optimal input torques of servos to minimize the cost function.
