首页|Studies from University of Quebec at Trois-Rivieres (UQTR) Update Current Data o n Robotics (An Efficient Indoor Large Map Global Path Planning for Robot Navigat ion)
Studies from University of Quebec at Trois-Rivieres (UQTR) Update Current Data o n Robotics (An Efficient Indoor Large Map Global Path Planning for Robot Navigat ion)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Current study results on Robotics have been published. According to news reportingfrom Trois-Rivieres, Canada, by New sRx journalists, research stated, “Large indoor cluttered environmentrepresenta tion is still a challenging task when non-uniform triangle cellbased or quadrang le cell-baseddecomposition is used to build the map. This paper aims at proposi ng a new method to represent a largeindoor environment for efficient and global robot path planning using a trade-off among three criteria: pathlength, distan ce to obstacles, and path search complexity.”
Trois-RivieresCanadaNorth and Centra l AmericaEmerging TechnologiesMachine LearningRobotRoboticsUniversity of Quebec at Trois-Rivieres (UQTR)
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