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基于模糊神经网络势场法的机器人动态路径规划
Robot dynamic path planning based on neural network fuzzy control artificial potential field method
【摘要】 针对机器人局部路径规划的特点和传统人工势场理论存在不足的问题,采用改进的斥力势场函数,将机器人与目标的相对距离和速度考虑在内以解决局部最小值问题。引入神经网络模糊系统,兼顾了系统的鲁棒性和快速性,并在应用实例中得到了有效的验证。
【Abstract】 According to the character of the robot path planning, we improved the conventional theory of artificial potential field, the relative distance between the robot and the goal was considered to solve the local minimum problem. By introducing neural networks into fuzzy system, the controller takes both system robustness and fastness into account and the effectiveness is verified in application.
【关键词】 神经模糊方法;
人工势场法;
路径规划;
【Key words】 neuro-fuzzy approach; artificial potential field method; path planning;
【Key words】 neuro-fuzzy approach; artificial potential field method; path planning;
- 【文献出处】 微型机与应用 ,Microcomputer & Its Applications , 编辑部邮箱 ,2011年11期
- 【分类号】TP242
- 【被引频次】1
- 【下载频次】215