Mobile Robot Navigation Using Particle Swarm Optimization and Adaptive NN

This paper presents a novel design for mobile robot using particle swarm optimization (PSO) and adaptive NN control. The adaptive NN control strategy guarantees that robot with nonholonomic constraints can follow smooth trajectories. Based on this property, a PSO algorithm for path planning is propo...

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Bibliographic Details
Published inAdvances in Natural Computation pp. 628 - 631
Main Authors Li, Yangmin, Chen, Xin
Format Book Chapter Conference Proceeding
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg 2005
Springer
SeriesLecture Notes in Computer Science
Subjects
Applied sciences
Artificial intelligence
Computer science; control theory; systems
Exact sciences and technology
Navigation
Moving robot
Evolutionary algorithm
Swarm intelligence
Path planning
Neural network
Trajectory
Adaptive control
Collision avoidance
Adaptive method
Robotics
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Summary:This paper presents a novel design for mobile robot using particle swarm optimization (PSO) and adaptive NN control. The adaptive NN control strategy guarantees that robot with nonholonomic constraints can follow smooth trajectories. Based on this property, a PSO algorithm for path planning is proposed. The path planning generates smooth path with low computational cost to avoid obstacles, so that robot can use smooth control strategy to track the trajectory.
ISBN:9783540283201
354028320X
3540283234
9783540283232
ISSN:0302-9743
1611-3349
DOI:10.1007/11539902_76