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

In 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 res...

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Bibliographic Details
Published inRobotica Vol. 37; no. 8; pp. 1363 - 1382
Main Authors Sathiya, V., Chinnadurai, M.
Format Journal Article
LanguageEnglish
Published Cambridge, UK Cambridge University Press 01.08.2019
Subjects
Actuators
Classification
Computer simulation
Evolutionary algorithms
Evolutionary computation
Genetic algorithms
Multiple objective analysis
Optimization
Optimization techniques
Robot dynamics
Robots
Sorting algorithms
Trajectory planning
Travel time
HMODE
NSGA-II
Wheeled mobile robot
Differential drive
Optimal trajectory
NURBS
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Summary:In 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.
ISSN:0263-5747
1469-8668
DOI:10.1017/S026357471800156X