Dynamic path planning for mobile robot based on genetic algorithm in unknown environment

Pu, Shi; Cui, Yujie

doi:10.1109/ccdc.2010.5498349

Cited by 30 publications

(17 citation statements)

References 8 publications

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“…At time t, the kth ant transfer probability from grid i to grid j can be expressed by Eq. (5). As the taboo table tabu k is the set of grids that ants walk through before, allowed k (t) is the absolute complement of tabu k in the set of subgrid (g).…”

Section: Ant's State Transformation Rulementioning

confidence: 99%

“…From the objective attraction function (5), it can be seen that the ant transfer probability is a trade-off between the heuristic and pheromone factor. Roulette wheel is used for the selection of the ant's next step.…”

Section: Ant's State Transformation Rulementioning

confidence: 99%

“…To solve the problem of path planning, some modern intelligent path planning algorithms, such as genetic algorithm (GA) [5][6][7], simulated annealing (SA) [8,9], neural network (NN) [10][11][12], particle swarm optimization (PSO) [13,14], and ant colony optimization (ACO) [15][16][17][18], are adopted. Among those approaches, the ACO is the only meta-heuristic approach inspired by the behaviour of the biological ants in real world.…”

Section: Introductionmentioning

confidence: 99%

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Route Optimization for Autonomous Container Truck Based on Rolling Window

Huang

Zheng

2016

International Journal of Advanced Robotic Systems

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Route optimization for autonomous container truck is one of the key problems to realize the automatic container port. An environment model for container truck is built by grid method. Considering the complex and unknown construction environment of the container port, an improved ant colony optimization (IACO) algorithm based on rolling window is proposed to achieve path planning for container truck. In the simulations, it is obvious that the IACO will not only achieve a safe collision avoidance path, the length of which is shorter than the truck's traditional route no matter how complex the environment is, but also show good analytical and disposing ability of dead ends in the path planning process. Compared with conventional ant colony optimization (ACO), the running time of IACO is shorter. The results of the simulation experiments demonstrate that the IACO is a good method which is applicable to route optimization for autonomous container truck.

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Section: Ant's State Transformation Rulementioning

confidence: 99%

Section: Ant's State Transformation Rulementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Route Optimization for Autonomous Container Truck Based on Rolling Window

Huang

Zheng

2016

International Journal of Advanced Robotic Systems

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“…Na maior parte da literatura, essas técnicas aplicam planejamento global, cujas rotasótimas são obtidas a um alto custo computacional; ou planejamento local, onde rotas subótimas são determi-Suporte financeiro: FAPEMIG e CNPq. nadas a um custo computacional mais baixo (Altaharwa et al, 2008;Shamsinejad et al, 2010;Yun et al, 2011;Shi and Cui, 2010;Tuncer and Yildirim, 2012).…”

Section: Introductionunclassified

Classificação de Ambientes com LiDAR-2D para Navegação em Robótica Móvel

Soares

Brandão

Lopes

2019

Anais Do 14º Simpósio Brasileiro De Automação Inteligente

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In mobile robotics, techniques for identification and classification of environments aim to assist in route planning. In this context, this work addresses the classification of environments through neural networks applied to readings of a 2D LiDAR on board a mobile robot. The proposed strategy presented a hit rate of more than 90% for the differentiation among room, open area, narrow corridor and wide corridor. The proposed system presents low computational cost, being a powerful and promising tool to assist in the local planning of navigation strategies. Resumo: Em robótica móvel, técnicas de identificação e classificação de ambientes visam auxiliar no planejamento de rotas. Neste contexto, este trabalho aborda a classificação de ambientes por meio redes neurais aplicadas a leituras de um LiDAR 2D a bordo de um robô. A estratégia proposta apresentou uma taxa de acerto superior a 90% para a diferenciação entre sala,área aberta, corredor estreito e corredor largo. O sistema proposto apresenta baixo custo computacional, sendo uma ferramenta poderosa e promissora para auxiliar no planejamento local de estratégias de navegação.

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“…A dynamic robot path planning schema for unknown environments is studied in [19]. In [20], GAs are used to generate the optimal path by exploiting the advantage of its strong optimization ability, leading to the proposal of a tailored genetic algorithm for optimal path planning.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Path Planning Algorithm for a Mobile Robot Based on Visible Space and an Improved Genetic Algorithm

Zhang

Zhao

Deng

et al. 2016

International Journal of Advanced Robotic Systems

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In this study, a series of new concepts and improved genetic operators of a genetic algorithm (GA) was proposed and applied to solve mobile robot (MR) path planning problems in dynamic environments. The proposed method has two superiorities: fast convergence towards the global optimum and the feasibility of all solutions in the population. Path planning aims to provide an optimal path from a starting location to a target location, preventing collision or so-called obstacle avoidance. Although GAs have been widely used in optimization problems and can obtain good results, conventional GAs have some weaknesses in an obstacle environment, such as infeasible paths. The main ideas in this paper are visible space, matrix coding and new mutation operators. In order to demonstrate the superiority of this method, three different obstacle environments have been used and an experiment is conducted. This algorithm is effective in both static and dynamic environments.

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Dynamic path planning for mobile robot based on genetic algorithm in unknown environment

Cited by 30 publications

References 8 publications

Route Optimization for Autonomous Container Truck Based on Rolling Window

Route Optimization for Autonomous Container Truck Based on Rolling Window

Classificação de Ambientes com LiDAR-2D para Navegação em Robótica Móvel

Dynamic Path Planning Algorithm for a Mobile Robot Based on Visible Space and an Improved Genetic Algorithm

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