Robotics & Machine Learning Daily News2024,Issue(Jun.20) :39-39.

Study Findings from Chinese Academy of Sciences Broaden Understanding of Robotic s (Tool Center Point Calibration Via Posturesequence Particle Swarm Optimizatio n)

中国科学院的研究成果拓宽了机器人S(基于姿态序列粒子群优化的工具中心点校准)的理解

Robotics & Machine Learning Daily News2024,Issue(Jun.20) :39-39.

Study Findings from Chinese Academy of Sciences Broaden Understanding of Robotic s (Tool Center Point Calibration Via Posturesequence Particle Swarm Optimizatio n)

中国科学院的研究成果拓宽了机器人S(基于姿态序列粒子群优化的工具中心点校准)的理解

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摘要

由一名新闻记者-机器人与机器学习的工作人员新闻编辑每日新闻-关于机器人的最新研究结果已经发表。根据NewsRx记者从沈阳发回的新闻报道,研究表明:“机器人的操作精度在很大程度上取决于工具中心点(TCP)的标定精度。本文提出了姿态序列粒子群算法(PS2O)用于T CP标定。”本研究经费来自中国博士后科学基金。本文首先分析了条件数和回归矩阵的最小e值对标定精度的影响机理,然后基于条件数、最小特征值和相邻姿态距离之和构造了多目标优化问题,最后给出了一个基于条件数和最小特征值的多目标优化问题。将粒子群优化算法(PSO)应用于所构造的多目标优化问题,得到了一个优化的姿态序列.仿真和实验表明,TCP标定误差可以用约束矩阵的条件数和最小特征值来表征,与随机姿态采样相比,优化的姿态采样使标定误差范数降低了38.66%.

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 from Shenyang, People's Republic of China, by NewsRx journalists, research stated, "Robots' manipulation accuracy i s heavily determined by the calibration accuracy of the tool center point (TCP). This article proposes posture-sequence particle swarm optimization (PS2O) for T CP calibration." Financial support for this research came from China Postdoctoral Science Foundat ion. The news correspondents obtained a quote from the research from the Chinese Acad emy of Sciences, "First, the mechanism of the condition number and the minimum e igenvalue of the regression matrix on the calibration accuracy are analyzed. Sec ond, a multiobjective optimization problem is constructed based on the condition number, the minimum eigenvalue, and the sum of adjacent posture distances. Fina lly, an optimized posture sequence is obtained by applying the particle swarm op timization (PSO) algorithm to the constructed multiobjective optimization proble m. Simulations and experiments demonstrate that the error of TCP calibration can be characterized by the condition number and the minimum eigenvalue of the regr ession matrix. Compared with random posture sampling, the optimized posture sequ ence for sampling reduces the norm of the calibration error by 38.66% ."

Key words

Shenyang/People's Republic of China/As ia/Emerging Technologies/Machine Learning/Nano-robot/Particle Swarm Optimiza tion/Robotics/Chinese Academy of Sciences

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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