Abstract
Automated guided vehicles (AGVs) are widely used for transporting materials in industry and commerce. In this research, an intelligent AGV-based material-handling system was developed using a model- based systems engineering (MBSE) approach. The core of the AGV, the controller, was designed in the system modelling language environment using Visual Paradigm software, and then implemented in the hardware. As the result, the AGV’s complex tasks of material handling, navigation, and communication were successfully accomplished and tested in the real industrial environment. The developed AGV is capable of towing trolleys with a weight of up to 200kg at walking speed. The AGV can be incorporated into an intelligent material-handling system with multiple autonomous vehicles and work stations, thus providing flexibility and reconfigurability for the whole manufacturing system. Ergonomic and safety aspects were also considered in the design of the AGV. A comprehensive safety system that is compliant with industrial standards was implemented.
Highlights
The use of mobile robots in industrial applications is growing in popularity, with companies such as Toyota [1,2] investing heavily in incorporating autonomous vehicles into the production process
The performance of the Automated guided vehicles (AGVs) controller with respect to path following, power monitoring, and safety was evaluated in the experiments
Each AGV performed tasks based on its own internal sequence, which proved that the AGVs are capable of operation even in the absence of the intelligent controller
Summary
The use of mobile robots in industrial applications is growing in popularity, with companies such as Toyota [1,2] investing heavily in incorporating autonomous vehicles into the production process. According to Stewart [4], the use of robotic rather than human workers has enabled the automotive industry to ensure that tasks are performed according to expectations. One of the main advantages of robotic workers is that they eliminate the need for humans to perform tasks that are dangerous to their health or are located in hazardous environments [4]. According to Floreano et al [6], smaller robots cost less than larger robots because they use smaller mechanical components and electronics, yet they perform comparably. The initial AGV design used an array of five induction sensors to detect the track laid out on the shop floor, providing a low-cost solution. In addition to the safety bumper, a laser sensor was installed to improve the overall safety of the AGV
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