摘要
针对复杂环境下机器人的路径规划问题,将蚁群优化算法引入这一新的应用领域,设计了相应的算法,解决了以前尚未涉足的带约束条件的连续函数优化问题.仿真结果验证了所设计算法的实用性和有效性.
In order to overcome the current difficulty of the existing algorithms in path planning for robots, the ant colony optimization algorithm is introduced into this new application area. The corresponding ant colony optimization algorithm is presented to solve the continuous function optimization problem containing constraint conditions. The numerical simulation shows the efficiencies of the algorithm.
出处
《控制与决策》
EI
CSCD
北大核心
2004年第2期166-170,共5页
Control and Decision
基金
国家自然科学基金资助项目(69975003).
关键词
蚁群优化(ACO)算法
机器人
路径规划
Algorithms
Computer simulation
Constraint theory
Motion planning
Optimization
