Robotics & Machine Learning Daily News2024,Issue(MAY.31) :100-100.

Studies from Fudan University Update Current Data on Robotics (Safe and Robust M otion Planning for Autonomous Navigation of Quadruped Robots in Cluttered Enviro nments)

Robotics & Machine Learning Daily News2024,Issue(MAY.31) :100-100.

Studies from Fudan University Update Current Data on Robotics (Safe and Robust M otion Planning for Autonomous Navigation of Quadruped Robots in Cluttered Enviro nments)

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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 originating from Shanghai, People’s Republic of China, by NewsRx editors, the research stated, “Quadruped robots, with their superior terrain adaptability and flexible movement capabilities, demonstrate gr eater application potential in complex environments compared to traditional grou nd robots.” The news editors obtained a quote from the research from Fudan University: “Howe ver, their nonnegligible body shape and anisotropic motion characteristics comp licate the achievement of high-precision motion planning and autonomous navigati on. In this paper, we propose a safe and robust motion planning system tailored for autonomous navigation of quadruped robots in cluttered environments. We adop t a hierarchical architecture and decompose the planning process into front-end searching and back-end optimization. In the front-end searching stage, the robot finds a smooth, feasible, and energy-efficient initial trajectory with safety c onsideration. In the back-end optimization stage, we leverage B-splines to enhan ce the trajectory smoothness, safety, and motion stability. Finally, the time al location is fine-tuned through iterative refinement, ensuring the feasibility of the optimized trajectory.”

Key words

Fudan University/Shanghai/People’s Rep ublic of China/Asia/Emerging Technologies/Machine Learning/Nano-robot/Robot ics

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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