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作 者:ZHANG ZiQiang CHEN DianSheng CHEN KeWei ZHANG ZiQiang;CHEN DianSheng;CHEN KeWei(Robotic Institute in School of Mechanical Engineering and Automation, Beihang University)
机构地区:[1]Robotic Institute in School of Mechanical Engineering and Automation, Beihang University
出 处:《Science China(Technological Sciences)》2016年第9期1413-1427,共15页中国科学(技术科学英文版)
基 金:supported by the National Natural Science Foundation of China(Grant No.51375035);the Specialized Research Fund for the Doctoral Program of Higher Education of China(Grant No.20121102110021)
摘 要:Good landing buffering performance can reduce impact and vibration for the bionic locust jumping robot; thus, a landing buffer is important in evaluating the motion performance of the bionic locust robot. In particular, the legs of the robot are the main structures that realize the buffer; thus, its structure affects buffering performance. Three typical leg structure models are established based on the physiological analysis of the locust leg and research status, namely, bionic leg, multi-constraint leg, and arc legs. Kinematic and force analyses are conducted for these types of legs. Particularly, flexible deformation of leg link is considered in the analysis to describe the movement process accurately. In order to compare the buffering performance of these types of legs quantitatively, the performance indices with maximum buffering distance, the energy absorption capability, and the mechanical property are presented. Based on the performance indices, the structure parameters are analyzed and optimized. The buffering performance of the three leg structures is compared with the comprehensive performance of different structures in each best state. This study offers a quantitative analysis and comparison for different legs of bionic locust jumping robot based on landing buffering performance. Furthermore, a theoretical basis for future research and engineering applications is established.
关 键 词:bionic locust robot leg model buffering performance parameter optimization comparison study
分 类 号:TP242[自动化与计算机技术—检测技术与自动化装置] TB484.1[自动化与计算机技术—控制科学与工程]
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