A moment estimation–based method for the path planning of manipulators with kinematic system reliability constraints

Author:

Wang Jin1,Wang Wei1ORCID,Fu Jianhui1,Lu Guodong1

Affiliation:

1. State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou, China

Abstract

Since the path planning plays a significant role in the manipulator’s control, the system reliability evaluation and optimization for path planning are studied with consideration of the joint clearance. A simple moment estimation–based method is proposed; a linear performance function is first established using the extreme value distribution theory. Based on the maximum entropy principle, the first four moments of variables are utilized to derive a best-fit probability density function to feature the characteristics of the system distribution rather than an empirical assumption of the normality. To meet the system reliability criterion constraints, a sensitivity analysis is conducted using the direct linearization method. With modification in the tolerance of sensitive parameters, the reliability can be improved efficiently. Traditional methods, such as the first-order second moment method, the first-order reliability method, and Monte Carlo simulation, are popular in this research field and therefore they are applied as benchmark methods for comprehensive comparisons in the accuracy and efficiency. A typical serial manipulator is applied as an example to validate the feasibility of our proposed method.

Funder

the China Postdoctoral Science Foundation

Fundamental Research Funds for the Central Universities

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

SAGE Publications

Subject

Mechanical Engineering

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