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A Comparative Study of Various Intelligent Algorithms based Path Planning for Mobile Robots
- Source :
- Engineering Journal, Vol 25, Iss 6 (2019)
- Publication Year :
- 2019
- Publisher :
- University of Baghdad, 2019.
-
Abstract
- In general, path-planning problem is one of most important task in the field of robotics. This paper describes the path-planning problem of mobile robot based on various metaheuristic algorithms. The suitable collision free path of a robot must satisfies certain optimization criteria such as feasibility, minimum path length, safety and smoothness and so on. In this research, various three approaches namely, PSO, Firefly and proposed hybrid FFCPSO are applied in static, known environment to solve the global path-planning problem in three cases. The first case used single mobile robot, the second case used three independent mobile robots and the third case applied three follow up mobile robot. Simulation results, which carried out using MATLAB 2014 environment, show the validity of the kinematic model for Nonholonomic mobile robot and demonstration that the proposed algorithm perform better than original PSO and FF algorithms under the same environmental constraints by providing the smoothness velocity and shortest path for each mobile robot.
- Subjects :
- Mathematical optimization
Computer science
business.industry
wheeled mobile robot, path planning, static environment, firefly algorithm, particle swarm optimization algorithm
Robotics
Mobile robot
02 engineering and technology
Computer Science::Robotics
Path length
lcsh:TA1-2040
Shortest path problem
Path (graph theory)
0202 electrical engineering, electronic engineering, information engineering
Robot
020201 artificial intelligence & image processing
Firefly algorithm
Artificial intelligence
Motion planning
business
lcsh:Engineering (General). Civil engineering (General)
Subjects
Details
- Language :
- Arabic
- ISSN :
- 25203339 and 17264073
- Volume :
- 25
- Issue :
- 6
- Database :
- OpenAIRE
- Journal :
- Engineering Journal
- Accession number :
- edsair.doi.dedup.....e37953ee10d998dc3802dcdbf849b48c