Findings from Johannes Kepler University Provide New Insights into Robotics (Ide ntification of Physically Consistent Dynamics Parameter of the Abb Irb 360-6/160 0 Delta Robot and Its Use for Timeoptimal Motion Planning Under Consideration o f ...)

Johannes Kepler大学的发现为机器人学提供了新的见解（Abb Irb 360-6/160 0 Delta机器人物理一致动力学参数的识别及其在考虑的时间最优运动规划中的应用）

Robotics & Machine Learning Daily News2024，Issue(Dec.3) ：74-74.

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Findings from Johannes Kepler University Provide New Insights into Robotics (Ide ntification of Physically Consistent Dynamics Parameter of the Abb Irb 360-6/160 0 Delta Robot and Its Use for Timeoptimal Motion Planning Under Consideration o f ...)

Johannes Kepler大学的发现为机器人学提供了新的见解（Abb Irb 360-6/160 0 Delta机器人物理一致动力学参数的识别及其在考虑的时间最优运动规划中的应用）

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摘要

由一名新闻记者-机器人与机器学习日报的工作人员新闻编辑每日新闻-调查人员讨论机器人的新发现。根据来自奥地利林茨，NewsRx记者，研究称，“基于模型的控制方案，向前动力学”仿真、合力计算和时间最优运动规划是其中的一个主要内容通常，它们都依赖于系统的动力学参数。动力学的物理一致性参数保证了质量矩阵的正定性和约束力的正确性。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators discuss new findings in Robotics. According to news reporting fromLinz, Austria, by NewsRx journalists, research stated, “Model-based control schemes, forward dynamicssimulations, co nstraint force computation and time-optimal motion planning have one major thing incommon, they all depend on the dynamics parameters of the system. Physical c onsistency of the dynamicsparameters ensures a positive definite mass matrix an d correct constraint forces.”

Key words

Linz/Austria/Europe/Emerging Technolo gies/Machine Learning/Robot/Robotics/Johannes Kepler University

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出版年

2024

Robotics & Machine Learning Daily News

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