Updated a year ago

虚实融合技术已经深入到各行各业,并得到了工业界的重视,尤其是在机器人领域。传统的机器人控制是通过平面界面利用鼠标、键盘控制的,对于机器人的灵活控制有很大的限制。而今随着AR 和AI 技术的出现,使得机器人灵活控制问题有了新的解决的思路和理论支撑。本文研究面向机械臂控制的虚实融合技术。以AR 为基础,通过使用机器人控制理论,结合深度图像识别技术和自然体感人机交互硬件,建立一套基于虚实融合技术的机械臂控制原型系统(ARCS)。
Composition of virtual-real worlds has been widely used in many domains.Especially to the industry in recent years,the typical human and mechanical interaction (HMI) has gradually been unable to meet the needs of current technological development. This thesis proposes an intelligence control system including robot control theory,deep learning for image recognition and gesture interaction.We call this system as Alpha Robot Control System (ARCS) .There are three main contributions. (1)The intelligent control model is proposed by combining the forward kinetics (FK) and the inverse kinetics (IK). They charge for the manual control and the automatic respectively. (2) The deep learning algorithm is proposed for image recognition. It is used to identify the goods and sort them in ARCS. (3) The hand gesture control is implemented through the smart hardware called leap motion. In the experiment, the results demonstrated that the proposed ARCS establishes a virtual platform for the next generation of human-machine interaction in digital twins for robot control.
Ning Xie
Associate Professor - Educator