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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Elshamli, A. Abdullah, H.A. Areibi, S. |
| Copyright Year | 2004 |
| Description | Author affiliation: Sch. of Eng., Guelph Univ., Ont., Canada (Elshamli, A.; Abdullah, H.A.; Areibi, S.) |
| Abstract | Optimization in dynamically changing environments is a hard problem. Path planning for mobile robots is a complex problem that not only guarantees a collision-free with minimum traveling distance but also requires smoothness and clearances. This paper presents a genetic algorithm approach for solving the path planning problem in stochastic mobile robot environments. The genetic algorithm planner (GAP) is based on a variable length representation, where different evolutionary operators are applied. A generic fitness function is used to combine all the objectives of the problem. In order to make the algorithm suitable for both static and dynamic environments, problem specific domain knowledge is used. |
| Sponsorship | Cisco Syst. General Elec. Ryerson Univ. AVFX Audio Visual Bell Canada Dofasco Dye & Durham Gennum Corp. IEEE Canada Found. Univ. of Toronto Niagara College of Appl. Arts and Technol |
| Starting Page | 677 |
| Ending Page | 680 |
| File Size | 259964 |
| Page Count | 4 |
| File Format | |
| ISBN | 0780382536 |
| ISSN | 08407789 |
| DOI | 10.1109/CCECE.2004.1345203 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2004-05-02 |
| Publisher Place | Canada |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Genetic algorithms Path planning Mobile robots Robotic assembly Safety Heuristic algorithms Robustness Stochastic processes Orbital robotics Manufacturing |
| Content Type | Text |
| Resource Type | Article |
| Subject | Electrical and Electronic Engineering Hardware and Architecture |
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