首页|Report Summarizes Robotics Study Findings from Hebei University of Technology (Design and Analysis of a Passive Adaptive Wallclimbing Robot On Variable Curvature Ship Facades)
Report Summarizes Robotics Study Findings from Hebei University of Technology (Design and Analysis of a Passive Adaptive Wallclimbing Robot On Variable Curvature Ship Facades)
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NETL
NSTL
Elsevier
Current study results on Robotics have been published. According to news reporting originating in Tianjin, People's Republic of China, by NewsRx journalists, research stated, "To improve the adaptive motion performance of traditional wall-climbing robots on variable-curvature facades, a crawlertype wall-climbing robot suitable for ship wall features is proposed by utilizing the advantages of passive mechanisms in realizing autonomous robots. The robot consists of two passive adaptive crawler mechanisms and a connecting module." Funders for this research include National Key Research and Devel-opment Project of China, Postgraduate Cultivation Funding Projects in Interdisciplinary Direction of Hebei University of Technology. The news reporters obtained a quote from the research from the Hebei University of Technology, "Each track structure contains multiple permanent magnets that can passively adapt to concave and convex facades of different curvatures. A static failure model is established according to the characteristics of the triangular distributed load, and the minimum adsorption force required for the robot to achieve safe motion is determined. The Halbach Array magnetic circuit design method was used to construct a gap-type permanent magnet adsorption model for lightweight design. The influence of wall thickness and air gap distance on the adsorption force is analyzed by parametric simulation." According to the news reporters, the research concluded: "The prototype platform test shows that the robot can realize adaptive variable curvature motion through passive adjustment of the mobile mechanism attitude and has a certain load capacity."
TianjinPeople's Republic of ChinaAsiaEmerging TechnologiesMachine LearningNano-robotRobotRoboticsHebei University of Technology
NETL
NSTL
Elsevier
