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机器人多指操作的抓取力分析和实时优化
引用本文:秦志强,赵锡芳,李泽湘,熊有伦.机器人多指操作的抓取力分析和实时优化[J].机械工程学报,2000,36(3):8-1216.
作者姓名:秦志强  赵锡芳  李泽湘  熊有伦
作者单位:1. 上海交通大学机器人研究所上海 200030
2. 香港科技大学
3. 华中理工大学
基金项目:国家863高技术机器人装配系统网点实验室和香港科技大学685/95E资助项目.
摘    要:在非线性摩擦锥约束转换为对称矩阵正定线性约束的基础上,首先将抓取力摩擦锥约束进一步转换为线性矩阵不等式约束,使抓取力封闭判别问题转化为带线性矩阵不等式约束的可行解问题,完成抓取的力封闭条件判别,然后根据摩擦锥的正定线性约束矩阵和抓取力平衡约束矩阵的分块特性和稀疏特性,实现多指滚动操作实时抓取力优化计算.最后在多指手实验平台上实现并验证了算法.

关 键 词:机器人  多指操作  力封闭  线性矩阵不等式  力优化
修稿时间:1998年12月18

CRITICAL HARDNESS WHEN HARD-DRY CUTTING GCr15 GRASPING FORCE ANALYSIS AND OPTIMIZATION FOR ROBOTIC MULTIFINGERED MANIPULATION
Qin Zhiqang,Zhao,Xifang.CRITICAL HARDNESS WHEN HARD-DRY CUTTING GCr15 GRASPING FORCE ANALYSIS AND OPTIMIZATION FOR ROBOTIC MULTIFINGERED MANIPULATION[J].Chinese Journal of Mechanical Engineering,2000,36(3):8-1216.
Authors:Qin Zhiqang  Zhao  Xifang
Affiliation:Qin Zhiqang Zhao Xifang (Shanghai Jiaotong University) Li Zexiang (Hong Kong University of Science and Technology) Xiong Youlun (Huazhong University of Science and Technology)
Abstract:Based on the early result that the nonlinear friction cone constraints are transformed into positive definiteness of certain symmetric matrices, further cast the friction cone constraints into linear matrix inequalities (LMIs) and formulate the force closure problem as an LMI feasibility problem. The latter was extensively studied in optimization and control scommunity and highly efficient algorithms with polynomial time complexity are now available for its solution. Then, with the observation that the linear constraint matrix of friction cone is sparse and constant, and only the linear constraint matrix of grasp map is dependent on the contact coordinates of the object, extend the grasping force optimization algorithm to realize the real-time grasping force optimization for multifingered manipulation with rolling contact. Finally, give the experiment results to verify the proposed algorithms on the multifingered hand platform.
Keywords:Robots Multifingered  manipulation Force  closure  Linear  matrix matrix inequalities Force optimization
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