Journal
INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL
Volume 13, Issue 6, Pages 1007-1031Publisher
CCC PUBL-AGORA UNIV
DOI: 10.15837/ijccc.2018.6.3370
Keywords
Membrane Computing; RENPSM; robotics; RRT; P-Lingua
Funding
- National Natural Science Foundation of China [61672437, 61702428]
- Sichuan Science and Technology Program [2018GZ0086, 2018GZ0185]
- Ministerio de Economia, Industria y Competitividad (MINECO) of Spain, through the Agencia Estatal de Investigacion (AEI)
- Fondo Europeo de Desarrollo Regional (FEDER) of the European Union
- [TIN2017-89842-P]
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Methods based on Rapidly-exploring Random Trees (RRTs) have been widely used in robotics to solve motion planning problems. On the other hand, in the membrane computing framework, models based on Enzymatic Numerical P systems (ENPS) have been applied to robot controllers, but today there is a lack of planning algorithms based on membrane computing for robotics. With this motivation, we provide a variant of ENPS called Random Enzymatic Numerical P systems with Proteins and Shared Memory (RENPSM) addressed to implement RRT algorithms and we illustrate it by simulating the bidirectional RRT algorithm. This paper is an extension of [21] a. The software presented in [21] was an ad-hoc simulator, i.e, a tool for simulating computations of one and only one model that has been hard-coded. The main contribution of this paper with respect to [21] is the introduction of a novel solution for membrane computing simulators based on automatic programming. First, we have extended the P-Lingua syntax -a language to define membrane computing models-to write RENPSM models. Second, we have implemented a new parser based on Flex and Bison to read RENPSM models and produce source code in C language for multicore processors with OpenMP. Finally, additional experiments are presented.
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