Robotics & Machine Learning Daily News2024,Issue(Oct.15) :121-122.

New Findings on Robotics from Beijing Institute of Technology Summarized (Effect ive Trajectory Generation for Robots On General 3d Curved Surface)

Robotics & Machine Learning Daily News2024,Issue(Oct.15) :121-122.

New Findings on Robotics from Beijing Institute of Technology Summarized (Effect ive Trajectory Generation for Robots On General 3d Curved Surface)

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Abstract

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 originating in Beijing, People’s Re public of China, by NewsRx journalists, research stated, “More and more robots a re required to adsorb or crawl on the 3D curved surface in order to assist human s in some dangerous or tedious tasks. Existing methods on curved surface are mer ely able to plan in 2.5D environment at best, limiting the applications of the r obots.” Funders for this research include National Natural Science Foundation of China ( NSFC), Beijing Natural Science Foundation. The news reporters obtained a quote from the research from the Beijing Institute of Technology, “In this letter, we propose an effective trajectory generation m ethod on general 3D curved surface. We utilize a pose projection strategy to eli minate terrain contact constraint such that it allows to address the 3D curved s urface path planning problem with current optimization solvers. We develop a rat ional terrain assessment approach based on the local terrain geometry, enabling a direct correlation with the robotic hardware properties. The smoothness and sa fety of the trajectory on 3D curved surface are significantly improved by optimi zing the projected state of the robots. We thoroughly validate our method in var ious scenarios.”

Key words

Beijing/People’s Republic of China/Asi a/Emerging Technologies/Machine Learning/Nano-robot/Robotics/Beijing Instit ute of Technology

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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