A neural dynamics based approach to real-time path planning and tracking control of a mobile robot

被引：0
|
作者：
Yang, SX [1 ]
Hu, Y [1 ]
Liu, PX [1 ]
Yuan, X [1 ]
Meng, MQH [1 ]
机构：
[1] Univ Guelph, Sch Engn, Guelph, ON N1G 2W1, Canada
来源：
PROCEEDINGS OF THE 2003 IEEE INTERNATIONAL SYMPOSIUM ON INTELLIGENT CONTROL | 2003年
关键词：
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Real-time collision-free path planning and tracking control of a nonholonomic mobile robot in a dynamic environment is investigated using a neural dynamics based approach. The real-time robot path is generated through a dynamic neural activity landscape of a topologically organized neural network that represents the changing environment. The dynamics of each neuron is characterized by an additive neural dynamics model. The real-time tracking velocities are generated by a novel tracking controller, which is also based on a shunting neural dynamics model. The effectiveness and efficiency of this approach are demonstrated through simulation studies.
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页码：258 / 263
页数：6
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