The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
본 논문에서는 자율 이동 로봇의 경로 계획 및 궤적 계획을 위한 유전자 알고리즘(GA)을 제안합니다. 우리의 GA 기반 접근 방식은 환경이 시간에 따라 변하거나 알 수 없는 경우에도 GA가 작동할 수 있다는 적응성의 장점이 있습니다. 따라서 오프라인 및 온라인 모션 계획 모두에 적합합니다. 먼저 2D 지형의 경로 계획을 위한 GA를 제시합니다. 무작위로 생성된 지형에서 GA의 성능과 적응성에 대한 시뮬레이션 결과가 표시됩니다. 그런 다음 경로 계획과 궤도 계획을 동시에 해결하기 위한 GA 확장에 대해 논의합니다.
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부
Kazuo SUGIHARA, John SMITH, "Genetic Algorithms for Adaptive Planning of Path and Trajectory of a Mobile Robot in 2D Terrains" in IEICE TRANSACTIONS on Information,
vol. E82-D, no. 1, pp. 309-317, January 1999, doi: .
Abstract: This paper proposes genetic algorithms (GAs) for path planning and trajectory planning of an autonomous mobile robot. Our GA-based approach has an advantage of adaptivity such that the GAs work even if an environment is time-varying or unknown. Therefore, it is suitable for both off-line and on-line motion planning. We first presents a GA for path planning in a 2D terrain. Simulation results on the performance and adaptivity of the GA on randomly generated terrains are shown. Then, we discuss an extension of the GA for solving both path planning and trajectory planning simultaneously.
URL: https://global.ieice.org/en_transactions/information/10.1587/e82-d_1_309/_p
부
@ARTICLE{e82-d_1_309,
author={Kazuo SUGIHARA, John SMITH, },
journal={IEICE TRANSACTIONS on Information},
title={Genetic Algorithms for Adaptive Planning of Path and Trajectory of a Mobile Robot in 2D Terrains},
year={1999},
volume={E82-D},
number={1},
pages={309-317},
abstract={This paper proposes genetic algorithms (GAs) for path planning and trajectory planning of an autonomous mobile robot. Our GA-based approach has an advantage of adaptivity such that the GAs work even if an environment is time-varying or unknown. Therefore, it is suitable for both off-line and on-line motion planning. We first presents a GA for path planning in a 2D terrain. Simulation results on the performance and adaptivity of the GA on randomly generated terrains are shown. Then, we discuss an extension of the GA for solving both path planning and trajectory planning simultaneously.},
keywords={},
doi={},
ISSN={},
month={January},}
부
TY - JOUR
TI - Genetic Algorithms for Adaptive Planning of Path and Trajectory of a Mobile Robot in 2D Terrains
T2 - IEICE TRANSACTIONS on Information
SP - 309
EP - 317
AU - Kazuo SUGIHARA
AU - John SMITH
PY - 1999
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E82-D
IS - 1
JA - IEICE TRANSACTIONS on Information
Y1 - January 1999
AB - This paper proposes genetic algorithms (GAs) for path planning and trajectory planning of an autonomous mobile robot. Our GA-based approach has an advantage of adaptivity such that the GAs work even if an environment is time-varying or unknown. Therefore, it is suitable for both off-line and on-line motion planning. We first presents a GA for path planning in a 2D terrain. Simulation results on the performance and adaptivity of the GA on randomly generated terrains are shown. Then, we discuss an extension of the GA for solving both path planning and trajectory planning simultaneously.
ER -