基于混合遗传算法的操作臂最优路径规划  

An Optimal Path Programming of the Manipulators Based on Hga

作　　者：朱兴龙[1] 周骥平[1] 

机构地区：[1]扬州大学机械工程学院,江苏扬州225009

出　　处：《机电产品开发与创新》2005年第2期14-16,共3页Development & Innovation of Machinery & Electrical Products

基　　金：江苏省高校自然科学基金(03KJB460161);江苏省科研基金(333工程)

摘　　要：提出了一种将小生境遗传算法与SWIFT算法相结合的混合遗传算法,用于冗余度操作臂的最优路径规划。针对目标物体在空间的位置和姿态确定的情况下,操作臂如何选择一条满足关节转角约束,且使所有关节转动角度之和为最小的最佳路径这一问题,给出了算法的实现过程。最后通过试验函数和9自由度操作臂的仿真结果,验证了该算法的正确性和可行性。A hybrid genetic algorithm for the path programming, which combined to SWIFT (Sequential Weight Increasing Factor Technique) algorithm and NGA (niche genetic algorithm), is presented in the paper. The process of the algorithm implementation the algorithm is described, which enables the plant (the sum of all joint revolute angle) to be minimal, and satisfies joint revolute angle constrained, when the initial position and pose of the goal is known. Finally, the feasibility and the validity of the algorithm are validated by the programming results of the test functions and the 9-DOF manipulator.

关 键 词：转角约束 路径规划 SWIFT算法 小生境遗传算法 

分 类 号：TP24[自动化与计算机技术—检测技术与自动化装置]