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.
翻译:本文使用模型预测控制(MPC)优化自由三方机器人臂的输入力,使其能精确地运行到目标位置并抓住物体。首先使用单镜相机来识别物体的颜色和深度。然后,通过坐标转换对物体进行反动能计算和空间坐标进行组合,以获得每个瑟沃所需的旋转角度。最后,生成了机器人臂结构的动态模型,并应用模型预测控制模拟服务器的最佳输入力,以尽量减少成本功能。