Kinematic calibration performance is heavily dependent on two factors-the ability of calibration configurations mapping kinematic parameter errors, and the un-modeled errors including joint clearance, thermal expansion, and measurement noise. Therefore, this paper deals with the calibration configuration optimization to reduce the impact of the two factors on calibration performance. We pay particular attention to establish an index for evaluating calibration configuration's quality. Different from other works, the proposed comprehensive quality index can simultaneously reflect configurations' observability and globality. Furthermore, the numerical methods are used to analyze the relationships between the comprehensive quality index and configuration number, and the relationships between calibration performance and configuration number. Based on the above relationships, we provide a feasible solution for determining the calibration configuration number of a specific manipulator. Based on the above work, configuration optimization model is established and solved by particle swarm optimization. The simulation of an eight degree-of-freedom manipulator illustrates the advantages of the proposed method. In 100 calibration simulations, optimized configurations perform better than random configurations, with the position accuracy increased by 43.86% and the attitude accuracy increased by 14.29%.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.