Motion planning of an autonomous mobile robot by integrating GAs and fuzzy logic control

Tzuu Hseng S. Li; Ming Sheng Chiang; Sheng Sung Jian

Motion planning of an autonomous mobile robot by integrating GAs and fuzzy logic control

Tzuu Hseng S. Li, Ming Sheng Chiang, Sheng Sung Jian

Department of Electrical Engineering

Research output: Contribution to conference › Paper › peer-review

12 Citations (Scopus)

Abstract

This paper is to determine the optimal motion planning for the autonomous mobile robot (AMR) moving in the environment with obstacles. We propose two motion planning methods, one is the linear vertex decision mechanism (LVDM) and the other one is the fuzzy logic decision mechanism (FLDM). Computer simulations are explored to compare the performance of these two mechanisms. Furthermore, we apply the genetic algorithms (GAs) to the LVDM to select the optimal weighting factor and we also adopt the GAs in the FLDM such that the best membership function and/or the number of fuzzy control rules can be obtained. The computer simulations of the evolved LVDM and FLDM with GAs are also provided. All the simulations demonstrate that the proposed schemes can indeed guide the AMR even the circumstance is filled with obstacles.

Original language	English
Pages	933-936
Number of pages	4
Publication status	Published - 2000 Jan 1
Event	FUZZ-IEEE 2000: 9th IEEE International Conference on Fuzzy Systems - San Antonio, TX, USA Duration: 2000 May 7 → 2000 May 10

Other

Other	FUZZ-IEEE 2000: 9th IEEE International Conference on Fuzzy Systems
City	San Antonio, TX, USA
Period	00-05-07 → 00-05-10

All Science Journal Classification (ASJC) codes

Software
Theoretical Computer Science
Artificial Intelligence
Applied Mathematics

Cite this

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title = "Motion planning of an autonomous mobile robot by integrating GAs and fuzzy logic control",

abstract = "This paper is to determine the optimal motion planning for the autonomous mobile robot (AMR) moving in the environment with obstacles. We propose two motion planning methods, one is the linear vertex decision mechanism (LVDM) and the other one is the fuzzy logic decision mechanism (FLDM). Computer simulations are explored to compare the performance of these two mechanisms. Furthermore, we apply the genetic algorithms (GAs) to the LVDM to select the optimal weighting factor and we also adopt the GAs in the FLDM such that the best membership function and/or the number of fuzzy control rules can be obtained. The computer simulations of the evolved LVDM and FLDM with GAs are also provided. All the simulations demonstrate that the proposed schemes can indeed guide the AMR even the circumstance is filled with obstacles.",

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N2 - This paper is to determine the optimal motion planning for the autonomous mobile robot (AMR) moving in the environment with obstacles. We propose two motion planning methods, one is the linear vertex decision mechanism (LVDM) and the other one is the fuzzy logic decision mechanism (FLDM). Computer simulations are explored to compare the performance of these two mechanisms. Furthermore, we apply the genetic algorithms (GAs) to the LVDM to select the optimal weighting factor and we also adopt the GAs in the FLDM such that the best membership function and/or the number of fuzzy control rules can be obtained. The computer simulations of the evolved LVDM and FLDM with GAs are also provided. All the simulations demonstrate that the proposed schemes can indeed guide the AMR even the circumstance is filled with obstacles.

AB - This paper is to determine the optimal motion planning for the autonomous mobile robot (AMR) moving in the environment with obstacles. We propose two motion planning methods, one is the linear vertex decision mechanism (LVDM) and the other one is the fuzzy logic decision mechanism (FLDM). Computer simulations are explored to compare the performance of these two mechanisms. Furthermore, we apply the genetic algorithms (GAs) to the LVDM to select the optimal weighting factor and we also adopt the GAs in the FLDM such that the best membership function and/or the number of fuzzy control rules can be obtained. The computer simulations of the evolved LVDM and FLDM with GAs are also provided. All the simulations demonstrate that the proposed schemes can indeed guide the AMR even the circumstance is filled with obstacles.

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Motion planning of an autonomous mobile robot by integrating GAs and fuzzy logic control

Abstract

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All Science Journal Classification (ASJC) codes

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