Multi Objective Optimization of Trajectory Planning of Non-holonomic Mobile Robot in Dynamic Environment Using Enhanced GA by Fuzzy Motion Control and A*

2014 ◽  
pp. 34-49 ◽  
Author(s):  
Bashra Kadhim Oleiwi ◽  
Rami Al-Jarrah ◽  
Hubert Roth ◽  
Bahaa I. Kazem
Keyword(s):  
Mobile Robot ◽  
Motion Control ◽  
Trajectory Planning ◽  
Dynamic Environment ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Holonomic Mobile Robot

Evolutionary Algorithms-Based Multi-Objective Optimal Mobile Robot Trajectory Planning

Robotica ◽  
2019 ◽  
Vol 37 (08) ◽  
pp. 1363-1382 ◽  
Author(s):  
V. Sathiya ◽  
M. Chinnadurai
Keyword(s):  
Mobile Robot ◽  
Differential Evolution ◽  
Trajectory Planning ◽  
Research Study ◽  
Research Problem ◽  
Optimization Techniques ◽  
Nsga Ii ◽  
Multi Objective ◽  
Robot Trajectory ◽  
New Variant

SummaryIn this research study, trajectory planning of mobile robot is accomplished using two techniques, namely, a new variant of multi-objective differential evolution (heterogeneous multi-objective differential evolution) and popular elitist non-dominated sorting genetic algorithm (NSGA-II). For this research problem, a wheeled mobile robot with differential drive is considered. A practical, feasible and optimal trajectory between two locations in the presence of obstacles is determined through the proposed algorithms. A safer path is obtained by optimizing certain objectives (travel time and actuators effort) taking into account the limitations of mobile robot’s geometric, kinematic and dynamic parameters. Robot motion is represented by a cubic NURBS trajectory curve. The capability of the proposed optimization techniques is analyzed through numerical simulations. Results ensure that the proposed techniques are more desirable for this problem.

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