Robotics & Machine Learning Daily News2024,Issue(Oct.2) :84-84.

School of Mechanical and Electrical Engineering Researchers Discuss Research in Robotic Systems (Research on a new method for the degree of freedom analysis of parallel mechanism)

Robotics & Machine Learning Daily News2024,Issue(Oct.2) :84-84.

School of Mechanical and Electrical Engineering Researchers Discuss Research in Robotic Systems (Research on a new method for the degree of freedom analysis of parallel mechanism)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Research findings on robotic systems a re discussed in a new report. According to news originating from Beijing, People ’s Republic of China, by NewsRx correspondents, research stated, “At present, tr aditional analysis methods sometimes show incompatibility when analyzing the deg ree of freedom (DOF) of parallel mechanisms.” Our news reporters obtained a quote from the research from School of Mechanical and Electrical Engineering: “In this research, a new DOF analysis method (MV-DOF method) based on primary-ancillary motion theory is developed. The 4PPRRR serie s-parallel mechanism is taken as an example, the analysis results by using the M V-DOF method are compared with those of traditional inverse helix theory and mod ified Grubler-Kutzbach formula, respectively. The comparison shows that this MV- DOF method can always analyze the DOF of the 4PPRRR series-parallel mechanism ac curately, while the other two traditional methods show inapplicability sometimes . During the analysis, an important rule is also found that the ancillary motion is equivalent to local constraint helix motion, but it is not always true in tu rn. Based on this MV-DOF method, a DOF cutting analysis way is also suggested. A ny output point on a complex mechanism can be taken as a cutting point, along wh ich the mechanism can be cut into two independent sub-mechanisms.”

Key words

School of Mechanical and Electrical Engi neering/Beijing/People’s Republic of China/Asia/Robotic Systems/Robotics

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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