首页|Researchers at South China University of Technology Publish New Data on Robotics (Towards Integration of IndoorGML and GDF for Robot Navigation in Warehouses)
Researchers at South China University of Technology Publish New Data on Robotics (Towards Integration of IndoorGML and GDF for Robot Navigation in Warehouses)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Current study results on robotics have been published. According to news reporting from Guangzhou, People's Republic o f China, by NewsRx journalists, research stated, "With the development of the na vigation technology, the outdoor navigation has made great progress, whereas the indoor navigation has some areas which is underdeveloped, insufficient to meet the rapidly increasing demands of people as well as the robotics." The news editors obtained a quote from the research from South China University of Technology: "Even though, the advance in indoor navigation technology still h as really brought a wide range of applications and a broad market, for instance, the flourishing intelligent warehouse system utilizes multi-robot operation whi ch have the certain requirement for an accurate indoor navigation system. As for the indoor navigation, the OGC standard IndoorGML has been released and undergo ing revision constantly. While the document really provides more advantageous su pport for the applications of Indoor Location-Based Services (LBS), in some aspe cts, especially the door-to-door navigation and the warehouse environment, it is not sufficiently adaptable, with still some room for improvement. IndoorGML is powerful for the common indoor scenarios like malls and offices, while as for ca refully-arranged warehouse environment and other large-scale operation scenarios with multi-robots that is more similar to an ordered system, it is obviously in sufficient. In this paper, we discuss about the potential to combination of Indo orGML and ITS standard ISO 20524 (GDF5.1), and extend the OGC standard indoorGML . We analyze the definition as well as function of related concepts, making some comparisons between these two standards."
South China University of TechnologyGu angzhouPeople's Republic of ChinaAsiaEmerging TechnologiesMachine Learni ngRobotRoboticsTechnology
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