Mobile robots can be used to transport freight, and this form of robot is referred to as an automated guided vehicle. In a manufacturing context, cargo management automation is critical. It is now possible because to recent advances in the fields of big data and artificial intelligence. Most cargoes are transported utilizing autonomously guided vehicles or labor, as we all know. Many autonomously guided vehicles go along pre-determined pathways that are usually marked with labels that are easily visible to vehicles. The deployment of autonomously guided vehicles is severely limited by the use of predetermined paths for vehicle navigation. For sensing and navigation, a few vehicles use high-precision Light Laser Detection and Ranging. A low-cost and precise strategy for mobile robots has been presented in this research. Because of the strong nonlinearity of UWB ranging data, a least square method is employed to locate ideal sites, and a gradient decent approach is employed to achieve rapid convergence. The use of defined courses for vehicle navigation substantially limits the deployment of autonomously guided vehicles. A few vehicles use high-precision Light Laser Detection and Ranging for sensing and navigation. In this study, a low-cost and precise technique for mobile robots is given. Because UWB range data is very nonlinear, a least square method is used to find optimum locations, and a gradient decent approach is used to achieve speedy convergence.
Author (s) DetailsDongqing Shi
Yiwu Industrial & Commercial College, Yiwu 322000, China and Yiwu Innovation Research Institute, Yiwu, 322000, China.
Haiyan Mi
Yiwu Industrial & Commercial College, Yiwu 322000, China.
View Book : https://stm.bookpi.org/CASTR-V2/article/view/1217
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