首页|Study Findings on Robotics Are Outlined in Reports from Harbin Institute of Tech nology (An Online Payload Identification Method Based On Parameter Difference fo r Industrial Robots)
Study Findings on Robotics Are Outlined in Reports from Harbin Institute of Tech nology (An Online Payload Identification Method Based On Parameter Difference fo r Industrial Robots)
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Current study results on Robotics have been published. According to news reporting out of Harbin, People's Republic of China, by NewsRx editors, research stated, "Accurate online estimation of the p ayload parameters benefits robot control. In the existing approaches, however, o n the one hand, only the linear friction model was used for online payload ident ification, which reduced the online estimation accuracy." Financial supporters for this research include National Key R&D Pro gram of China, National Natural Science Foundation of China (NSFC), Pre-research Task of State Key Laboratory of Robotics and Systems (HIT). Our news journalists obtained a quote from the research from the Harbin Institut e of Technology, "On the other hand, the estimation models contain much noise be cause of using actual joint trajectory signals. In this article, a new estimatio n algorithm based on parameter difference for the payload dynamics is proposed. This method uses a nonlinear friction model for the online payload estimation in stead of the traditionally linear one. In addition, it considers the commanded j oint trajectory signals as the computation input to reduce the model noise. The main contribution of this article is to derive a symbolic relationship between t he parameter difference and the payload parameters and then apply it to the onli ne payload estimation. The robot base parameters without payload were identified offline and regarded as the prior information. The one with payload can be solv ed online by the recursive least squares method. The dynamics of the payload can be then solved online based on the numerical difference of the two parameter se ts. Finally, experimental comparisons and a manual guidance application experime nt are shown."
HarbinPeople's Republic of ChinaAsiaEmerging TechnologiesMachine LearningNano-robotRobotRoboticsHarbin I nstitute of Technology
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