华南理工大学学报(自然科学版) ›› 2015, Vol. 43 ›› Issue (7): 124-129.doi: 10.3969/j.issn.1000-565X.2015.07.017

• 机械工程 • 上一篇    下一篇

机器人多指手抓取爆炸物能力研究

莫海军 林志生   

  1. 华南理工大学 机械与汽车工程学院,广东 广州 510640
  • 收稿日期:2014-12-08 修回日期:2015-01-23 出版日期:2015-07-25 发布日期:2015-06-03
  • 通信作者: 莫海军( 1966-) ,男,博士,副教授,主要从事机器人多指手抓取及排爆机器人研究. E-mail:mohj@scut.edu.cn
  • 作者简介:莫海军( 1966-) ,男,博士,副教授,主要从事机器人多指手抓取及排爆机器人研究.
  • 基金资助:
    国家自然科学基金资助项目( 51175182)

Investigation into the Ability of Multi-Fingered Dexterous Hand to Grasp an Explosive

 Mo Hai-jun Lin Zhi-sheng   

  1.  School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou 510640, Guangdong, China
  • Received:2014-12-08 Revised:2015-01-23 Online:2015-07-25 Published:2015-06-03
  • Contact: 莫海军( 1966-) ,男,博士,副教授,主要从事机器人多指手抓取及排爆机器人研究. E-mail:mohj@scut.edu.cn
  • About author:莫海军( 1966-) ,男,博士,副教授,主要从事机器人多指手抓取及排爆机器人研究.
  • Supported by:
     Supported by the National Natural Science Foundation of China( 51175182)

摘要: 应用力螺旋理论建立了多指手抓取矩阵与外力螺旋之间的关系,对多指手抓取 爆炸物能力进行研究. 首先建立多指手抓取爆炸物的力学模型,确定影响抓取的参数; 然 后以最大抓取重量为目标函数,建立满足力封闭约束条件下的抓取数学模型,并采用神经 网络和优化方法对多指手抓取爆炸物进行了仿真,研究多指手不同抓取位置与爆炸物重 量之间的对应关系,获得了多指手抓取爆炸物时最有利的抓取位置.

关键词: 机器人多指手, 抓取能力, 神经网络, 爆炸物

Abstract: On the basis of the force screw theory, the relationship between the grasp matrix of multi-fingered dexterous hand and the external force screw is established to investigate the ability of multi-fingered dexterous hand to grasp an explosive. Firstly, a mechanical model of multi-fingered dexterous hand which can grasp an explosive is constructed and the parameters influencing the grasp are determined. Then, with the maximum grasp being the goal, a mathematical model of the grasp is constructed under the constraint of force closure. Finally, through the neural network and optimization methods, the multi-fingered dexterous hand grasping an explosive is simulated, so as to reveal corresponding the relationship between the grasp position and the explosive weight. Thus, the best grasp position is obtained.

Key words: multi-fingered dexterous hand, grasp ability, neural networks, explosive

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