[1]陈魁 刘久富 苏青琴 刘蓉.基于Markov对策的机械臂二维路径规划[J].计算机技术与发展,2012,(05):57-59.
 CHEN Kui,LIU Jiu-fu,SU Qing-qin,et al.Markov Games Based Robot Arm 2D Path Planning[J].,2012,(05):57-59.
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基于Markov对策的机械臂二维路径规划()
分享到:

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2012年05期
页码:
57-59
栏目:
智能、算法、系统工程
出版日期:
1900-01-01

文章信息/Info

Title:
Markov Games Based Robot Arm 2D Path Planning
文章编号:
1673-629X(2012)05-0057-03
作者:
陈魁 刘久富 苏青琴 刘蓉
南京航空航天大学自动化学院
Author(s):
CHEN Kui LIU Jiu-fu SU Qing-qin LIU Rong
College of Automation, Nanjing University of Aeronautics and Astronautics
关键词:
多关节机器人机械臂多Agent系统Markov对策Nash均衡
Keywords:
multi-joint robot robot arm multi-Agent system Markov game Nash equilibrium
分类号:
TP18
文献标志码:
A
摘要:
针对机械臂应用环境状况较复杂、不确定条件较多,文中使用基于Markov对策的算法对二维机械臂进行路径规划。二维机械臂路径规划是三维多关节机器人规划的基础。首先根据实际的工作环境设定机械臂的运动范围并选择经常出现的动作组合作为机械臂运动的基本行为集,给出各种情况可能获得的报酬,依据多智能体Q值学习算法更新每个关节的报酬值,反解出对应最大报酬值的动作组合。文中仿真绘制最佳动作组合时的运动轨迹,分别仿真绘制机械臂运动环境中无障碍与放置圆形障碍物时的二维运动轨迹,并确定轨迹的误差
Abstract:
Use the algorithm based on Markov games to do path-planning for 2D robot arm in connection with its complex application en- vironment and more uncertain conditions. Path-planning for 2D robot arm is the basis of 3D path-planning. According to the actual work environment, set the ann's range of motion and select the common movements as the basic behavior set. Under kinds of conditions, the profits were shown. Then the profit of each joint was updated by the multi-agent Q-learning algorithm,and the formulas of movement's inverse kinematics are obtained. So the complexity of the algorithm is also reduced. It shows the best combination of trail, respectively, to draw the 2D motion trail in the case of barrier-free and a round obstacle,and then confirm the error of trail

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备注/Memo

备注/Memo:
国家自然科学基金(60674100);南京航空航天大学基本科研业务费专项科研项目(NS2010069)陈魁(1986-),男,河南汝南人,硕士研究生,研究方向为嵌入式系统与人工智能;刘久富,博士,研究方向为计算机科学与软件测试技术
更新日期/Last Update: 1900-01-01