Qian Jun, Zi Bin, Wang Daoming, Ma Yangang, Zhang Dan
School of Mechanical Engineering, Hefei University of Technology, 193 Tunxi Road, Hefei 230009, China.
Lassonde School of Engineering, York University, 4700 Keele Street, Toronto, ON M3J 1P3, Canada.
Sensors (Basel). 2017 Sep 10;17(9):2073. doi: 10.3390/s17092073.
In order to transport materials flexibly and smoothly in a tight plant environment, an omni-directional mobile robot based on four Mecanum wheels was designed. The mechanical system of the mobile robot is made up of three separable layers so as to simplify its combination and reorganization. Each modularized wheel was installed on a vertical suspension mechanism, which ensures the moving stability and keeps the distances of four wheels invariable. The control system consists of two-level controllers that implement motion control and multi-sensor data processing, respectively. In order to make the mobile robot navigate in an unknown semi-structured indoor environment, the data from a Kinect visual sensor and four wheel encoders were fused to localize the mobile robot using an extended Kalman filter with specific processing. Finally, the mobile robot was integrated in an intelligent manufacturing system for material conveying. Experimental results show that the omni-directional mobile robot can move stably and autonomously in an indoor environment and in industrial fields.
为了在紧凑的工厂环境中灵活、顺畅地运输物料，设计了一种基于四个麦克纳姆轮的全方位移动机器人。移动机器人的机械系统由三个可分离的层次组成，以便简化其组合和重组。每个模块化轮子安装在一个垂直悬挂机构上，这确保了移动的稳定性并保持四个轮子的间距不变。控制系统由两级控制器组成，分别实现运动控制和多传感器数据处理。为了使移动机器人在未知的半结构化室内环境中导航，将来自Kinect视觉传感器和四个车轮编码器的数据进行融合，使用扩展卡尔曼滤波器并经过特定处理来对移动机器人进行定位。最后，将移动机器人集成到用于物料输送的智能制造系统中。实验结果表明，该全方位移动机器人能够在室内环境和工业领域中稳定、自主地移动。
