Ponencia
Solving the feasibility problem in robotic motion planning by means of Enzymatic Numerical P systems
Autor/es | Pérez Hurtado de Mendoza, Ignacio
Martínez del Amor, Miguel Ángel Zhang, Gexiang Neri, Ferrante Pérez Jiménez, Mario de Jesús |
Departamento | Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial |
Fecha de publicación | 2019 |
Fecha de depósito | 2021-11-24 |
Publicado en |
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Resumen | Solving the feasibility problem in robotic motion planning means to
find feasible trajectories for specific mobile robots acting in environments with
obstacles whose positions are known a priori. The Rapidly-exploring ... Solving the feasibility problem in robotic motion planning means to find feasible trajectories for specific mobile robots acting in environments with obstacles whose positions are known a priori. The Rapidly-exploring Random Tree (RRT) algorithm is a classical algorithm to solve such a problem in real-life applications. In this paper, we provide a model in the framework of Enzymatic Numerical P systems to reproduce the behaviour of the RRT algorithm. A C++ ad-hoc simulator is also provided to validate the model. |
Agencias financiadoras | Ministerio de Economia, Industria y Competitividad (MINECO). España |
Identificador del proyecto | TIN2017-89842-P |
Cita | Pérez Hurtado de Mendoza, I., Martínez del Amor, M.Á., Zhang, G., Neri, F. y Pérez Jiménez, M.d.J. (2019). Solving the feasibility problem in robotic motion planning by means of Enzymatic Numerical P systems. En ACMC 2019: The 8th Asian Conference on Membrane Computing (152-165), Xiamen, China: IMCS: International Membrane Computing Society. |
Ficheros | Tamaño | Formato | Ver | Descripción |
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ACMC2019.pdf | 7.182Mb | [PDF] | Ver/ | |